Balancing a distributed system by replacing overloaded servers

ABSTRACT

Load-balancing a distributed system by replacing overloaded servers, including the steps of retrieving, by an assembling device using a fragment pull protocol, erasure-coded fragments associated with segments, from a set of fractional-storage servers. Occasionally, while retrieving the fragments, identifying at least one server from the set that is loaded to a degree requiring replacement, and replacing, using the fragment pull protocol, the identified server with a substitute server that is not loaded to the degree requiring replacement. Wherein the substitute server and the remaining servers of the set are capable of delivering enough erasure-coded fragments in the course of reconstructing the segments.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional PatentApplication No. 61/105,683, filed Oct. 15, 2008, and U.S. ProvisionalPatent Application No. 61,251,437, filed Oct. 14, 2009.

BACKGROUND

A distributed system usually stores redundant data, which is utilized byits load balancing process. In theory, the more redundant the data, theeasier it is to balance the distributed system. However, load balancinga distributed content delivery system is usually a complex task, whichmay require inter-server synchronization.

BRIEF SUMMARY

In one embodiment, a method for load-balancing fractional-storageservers, comprising: retrieving, by an assembling device using afragment pull protocol, erasure-coded fragments associated withsegments, from a set of fractional-storage servers; occasionally, whileretrieving the fragments, identifying at least one server from the setthat is loaded to a degree requiring replacement; and replacing, usingthe fragment pull protocol, the identified server with a substituteserver that is not loaded to the degree requiring replacement; whereinthe substitute server and the remaining servers of the set are capableof delivering enough erasure-coded fragments needed in the course ofreconstructing the segments.

In one embodiment, a method for load balancing fractional-storageservers, comprising: retrieving, by assembling devices using a fragmentpull protocol, erasure-coded fragments from a first set offractional-storage servers; identifying a second set of servers that areable to increase their current fragment delivery throughput;identifying, while retrieving the fragments, at least one server fromthe first set that is loaded beyond a certain threshold; and replacingthe server loaded beyond the certain threshold with a server selectedfrom the second set according to an algorithm.

In one embodiment, a system comprising: at least 100 fractional-storageCDN servers connected to the public Internet; the servers store, at anaverage storage gain >5, erasure-coded fragments associated withapproximately sequential segments of streaming contents, and areconfigured to respond with fragments to fragment pull protocol requestsissued by assembling devices; wherein the erasure-coded fragmentssupport source-selection diversity, and the system is configured toachieve load-balancing by directing the fragment pull protocol requeststowards the less loaded servers.

Implementations of the disclosed embodiments involve performing orcompleting selected tasks or steps manually, semi-automatically, fullyautomatically, and/or a combination thereof. Moreover, depending uponactual instrumentation and/or equipment used for implementing thedisclosed embodiments, several embodiments could be achieved byhardware, by software, by firmware, or a combination thereof. Inparticular, with hardware, embodiments of the invention could exist byvariations in the physical structure. Additionally, or alternatively,with software, selected functions of the invention could be performed bya data processor, such as a computing platform, executing softwareinstructions or protocols using any suitable computer operating system.Moreover, features of the embodiments may be combined.

BRIEF DESCRIPTION OF THE DRAWINGS

The embodiments are herein described, by way of example only, withreference to the accompanying drawings. No attempt is made to showstructural details of the embodiments in more detail than is necessaryfor a fundamental understanding of the embodiments. In the drawings:

FIG. 1 illustrates fractional-storage servers having the same bandwidthcapability.

FIG. 2 illustrates fractional-storage servers having different bandwidthcapabilities.

FIG. 3 and FIG. 4 illustrate a case where a fractional-storage serverhas failed.

FIG. 5 illustrates a server failure due to network congestion.

FIG. 6A is a flow diagram of one method in accordance with oneembodiment.

FIG. 6B is a flow diagram of one method in accordance with oneembodiment.

FIG. 7 illustrates retrieving fragments according to locality.

FIG. 8 illustrates one embodiment of segmenting content, encoding thesegments into erasure-coded fragments, distributing the fragments tofractional-storage servers, and obtaining the fragments by assemblingdevices and assembling servers.

FIG. 9 and FIG. 10 illustrate different embodiments of contentsegmentation.

FIG. 11 illustrates distribution and storage of erasure-coded fragmentson fractional-storage servers.

FIG. 12 illustrates three examples of changes made to redundancy factorsaccording to changes in demand.

FIG. 13 to FIG. 15 illustrate changes in content consumption.

FIG. 16 illustrates utilization of the entire aggregated bandwidth offractional-storage servers for multiple content delivery.

FIG. 17 illustrates fractional-storage servers placed at differentlocations.

FIG. 18 illustrate one embodiment where a data center hostingfractional-storage servers has failed and is replaced by a differentdata center.

FIG. 19 and FIG. 20 illustrate operation of multi data-center CDN.

FIG. 21 illustrates an assembling device obtaining erasure-codedfragments from fractional-storage servers.

FIG. 22 illustrates real time fragment retrieval, segmentreconstruction, and content presentation.

FIG. 23 to FIG. 26 illustrate various embodiments of fragment pullprotocols.

FIG. 27 illustrates geographically distributed fractional-storageservers.

FIG. 28 illustrates peak-to-average traffic ratios generated byassembling devices distributed over different time zones.

FIG. 29 illustrates US-based fractional-storage servers deliveringerasure-coded fragments to assembling devices spread over the globe.

FIG. 30 illustrates different loads at different times for differenttime zones.

FIG. 31 illustrates data centers communicating via shared links.

FIG. 32 illustrates fractional-storage servers communicating via sharednetworks.

FIG. 33 to FIG. 35 illustrate the influence of selecting source serverson backbone traffic.

FIG. 36 illustrates server selection for network path determination.

FIG. 37 illustrates fractional-storage servers located on the Internetbackbone.

FIG. 38 illustrates an assembling server located at a network juncture.And

FIG. 39 illustrates boosting fractional-storage servers' bandwidth usingP2P devices.

DETAILED DESCRIPTION

FIG. 1 illustrates one example of a fractional-storage system comprisingservers 699 a to 699(N) having a bandwidth capability 681. In otherwords, no server can send data at a rate higher than 681. Assemblingdevice 661 can select from which servers to obtain erasure-codedfragments for reconstruction of a segment. In one example, each serverstores one relevant, unique, erasure-coded fragment. Therefore, from theN servers storing N possible unique fragments, the assembling deviceneeds only K erasure-coded fragments for complete reconstruction of thesegment (K<N). Since it is not important which K fragments from the Nare retrieved, the assembling device may retrieve from the least loadedservers, so as to keep the load between the different servers balanced.When many assembling devices assemble contents in parallel, and sinceall assembling devices can select the least loaded servers, the endeffect is that the load on the servers is balanced, with the potentialfor most servers to approach their maximal bandwidth capabilities.Optionally, that load balancing is achieved without significantcoordination between the servers.

In the example of FIG. 1, assuming that K=3, the assembling device 661may select servers 699 b, 699(N−1), and 699 a for fragment retrieval, asthey have the lowest load of all N servers. Servers 699 c and 699(N), asan example, will not be chosen, as they have relatively higher loads.

The assembling device may select the least loaded servers using anyappropriate method, such as, but not limited to (i) accessing a centralcontrol server having data about the load conditions on the variousservers, or (ii) periodically querying the various servers on their loadconditions.

In one embodiment, instead of, or in addition to, selecting the leastloaded servers, the assembling device 661 tries a random set of Kservers from the N, and retrieves erasure-coded fragments from allservers reporting a load below a threshold, while higher loaded serverswill be replaced by least loaded servers from the possible N servers.The end result is that the server array is balanced because the Kerasure-coded fragments are retrieved from servers loaded below thethreshold.

In one embodiment, the assembling device does not know which of theservers store erasure-coded fragments related to the content to beretrieved, but the assembling device knows over how many servers (fromthe total number) the erasure-coded fragments are distributed.Therefore, the assembling device compensates for the infertile requestsby enlarging the number of requests for erasure-coded fragments.Optionally, the requested servers are selected based on approximatelyrandom algorithm.

The term “approximately random” as used herein refers to, but is notlimited to, random, pseudo random, and/or based on a long list ofnumbers featuring very low autocorrelation and very low correlation withother similar lists of numbers.

FIG. 2 illustrates one embodiment of different servers 698 a to 698(N)having different bandwidth capabilities of 683 a to 683(N)correspondingly. Assembling device 661 selects from which K servers, outof the possible N, to retrieve the fragments for segment reconstruction,wherein each server may have different unutilized bandwidth anddifferent bandwidth capability. When many assembling devices assemblecontents in parallel, while rejecting servers with a high load, the endeffect is that the server array is approximately balanced and mostservers can approach their maximal bandwidth capabilities. In oneembodiment, the server array is balanced by enabling many assemblingdevices to select the least loaded servers.

Still referring to FIG. 2, in the example, and assuming that K=3,servers 698 a, 698(N−1) and 698(N) will be selected, as they have thehighest unutilized bandwidth. In another example, the servers having thehighest percentage of unutilized bandwidth will be selected.

In one embodiment, servers 698 a to 698(N) represent completelydifferent types of server hardware, operating systems and capabilities,all put together in an array, and achieving load balance without theneed for significant inter-server coordination. In one example, thefragments are distributed to at least two different classes of servers;the first class comprises high bandwidth CDN servers directly connectedto the Internet backbone, and the second class comprises lower bandwidthCDN servers not directly connected to the Internet backbone.

In one embodiment, the servers are selected for fragment retrievalaccording to their unutilized fragment delivery bandwidth. For example,the servers report their unutilized bandwidth, and the assemblingdevices, or a control server, obtain the report and decide which serversto use for fragment delivery based on the unutilized bandwidth of eachserver.

In one embodiment, the servers are selected for fragment retrievalaccording to their ability to support additional fragment delivery load.For example, the servers report their ability to support additionalfragment delivery loads. And the assembling devices, or a controlserver, obtain the report, and select the servers that report an abilityto support additional fragment delivery loads.

In one embodiment, the assembling device, or a control server, looks fora pool of servers that may be used as replacements for servers that areloaded to a degree that does not allow continuation of fragmentdelivery. For example, the assembling device looks for potentialunloaded servers, while retrieving fragments from other servers. Theassembling device may sample relevant servers approximately randomly,and/or according to indications from a control server. The samplingprocess may comprise querying the potential server for load information,or measuring the latency or latency variance to the servers in order toestimate the current load on the server.

It is noted that in some of the disclosed embodiments the storage gainof each segment on each server and the amount of fragments obtained fromeach server by each assembling device may be independent of thebandwidth capability of the server, and that the ability to load balanceservers with different bandwidth capabilities/availabilities may notrequire adjustments of either storage gain or the number of fragmentsobtained from each server.

In one embodiment, the amount of unutilized fragment delivery bandwidth,or the fragment delivery bandwidth capability of at least some of theservers changes on-the-fly. The assembling devices compensate for thechanges approximately in real time by obtaining fragments from servershaving enough unutilized bandwidth to provide the requested fragments.

In one embodiment, a server that is loaded to a degree requiringreplacement indicates so by responding to a fragment request, or afragment load query.

In one embodiment, it is desired to replace one or more servers by otherservers for the delivery of erasure-coded fragments, wherein thereplacement servers are selected using a second criterion from a pool ofservers identified using a first criterion. For example, the firstcriterion for identifying the pool of replacement servers compriseslooking for servers capable of increasing their fragment deliverythroughputs, and the second criterion for selecting the replacementservers from the pool comprises selecting the best latency responseserver from the pool. In one example, the first criterion is a latencycriterion, and the second criterion is a load criterion. In anotherexample, the first criterion is a latency criterion, and the secondcriterion is a latency variance criterion. In another example, thesecond criterion is an approximately random selection. In oneembodiment, a server selected using the second criterion is compared tothe server to be replaced based on the second criterion. For example,the second criterion is latency, and the replacing server, selected fromthe pool, has a smaller latency than the server it replaces.

In one embodiment, the server to be replaced is identified by comparingthe actual performance level of the server with a threshold performancelevel. For example, when the compared performance is latency, a serverhaving response latency above a certain threshold is replaced. Inanother example, the compared performance is the load on the server,which may be measured in terms of the amount of the unutilized fragmentdelivery bandwidth, or in terms of the percent of the server'sunutilized fragment delivery bandwidth, or measured by any otherappropriate technique.

In some embodiments, the assembling devices use a fragment pull protocolto retrieve the fragments and approach the servicing servers. In someembodiments, the assembling devices use a push protocol to obtain thefragments and approach the servicing servers, possibly by obtainingmultiple sub-transmissions comprising fragment sequences.

The term “erasure coding” as used herein denotes a process in which asequence of erasure-coded fragments can be generated from a segment suchthat the segment can be reconstructed from any or almost any subset ofthe erasure-coded fragments of size equal to or somewhat larger than thesize of the segment (sometimes may be referred to as “enougherasure-coded fragments” or “sufficient subset of fragments”). Examplesof erasure codes include, but are not limited to, rateless codes,Reed-Solomon codes, Tornado codes, Viterbi codes, Turbo codes, any Blockcodes, any Convolutional codes, and any other codes that are usuallyused for forward error correction (FEC).

The term “rateless coding” as used herein denotes a type of erasurecoding in which a very long, potentially limitless, sequence ofrateless-coded fragments can be generated from a segment such that thesegment can be reconstructed from any or almost any subset of therateless-coded fragments of size equal to or somewhat larger than thesize of the segment (sometimes may be referred to as “enoughrateless-coded fragments”). Examples of rateless codes include, but arenot limited to, Raptor codes, LT codes, online codes, any Fountaincodes, and any other Rateless codes.

The term “erasure-coded fragment” denotes a fragment comprising dataencoded with an erasure code (which may also be a rateless code in someembodiments). The term “rateless-coded fragment” denotes a fragmentcomprising data encoded with a rateless code.

The term “assembling device” as used herein denotes a computing devicethat retrieves erasure-coded fragments from servers over a network. Theassembling device may perform one or more of the following: (i) Decodethe retrieved erasure-coded fragments into segments. (ii) Present thecontent reconstructed from the retrieved erasure-coded fragments. (iii)Act as a bandwidth amplification device, by receiving, storing, andforwarding erasure-coded fragments. In some embodiments, the assemblingdevice may be any device located at the user premises, like an STB, PC,gaming console, DVD player, PVR device, or any other device able toretrieve erasure-coded fragments from a communication network. In someembodiments, the assembling device may be an assembling server. In someembodiments, the assembling device may be any computational device withaccess to a communication network, located at a central office, datacenter, BRAS location, ISP premises, or any other place with directnetwork connectivity. In one embodiment, the assembling device iscoupled to a display device used for content presentation.

The abbreviation CDN denotes “Content Delivery Network”. The term “CDNserver” as used herein denotes a server having one or more of thefollowing characteristics: (i) A bandwidth (CDN_BW) that is much greaterthan the average bandwidth consumed by a user premises device (User_BW)receiving video streaming content. In some examples, the CDN_BW is atleast 10 times, 100 times, 1,000 times, or 10,000 times greater than theUser_BW. (ii) The server is located outside the last mile communicationinfrastructure of the end users, such that the CDN server and the endusers are located in different networks. For example, the CDN server isnot located under a BRAS, while the end users are located under a BRAS.Moreover, in some embodiments, the CDN servers are deployed over a widearea across the Internet and optionally located close to or on theInternet backbone. In some embodiments, the CDN server does not usuallyretrieve and play streaming content. In some embodiments, the CDN serverhas a much greater storage space than the storage space of an averageplayer of streaming content.

The term “fractional-storage server” in the context of erasure-codedfragments (also applicable to “fractional-storage CDN server”), as usedherein denotes a server that (i) stores less than the minimum quantityof erasure-coded fragments required to decode the erasure-codedfragments, and (ii) where at least a meaningful quantity of the storederasure-coded fragments is not stored in order to be consumed by thefractional-storage server.

The term “streaming content” as used herein denotes any type of contentthat can begin playing as it is being delivered. Streaming content maybe delivered using a streaming protocol, a progressive downloadprotocol, or any other protocol enabling a client to begin playing thecontent as it is being delivered. Moreover, the term “streamingprotocol” includes “progressive download protocol”. In addition, theverb “streaming” refers to using a streaming protocol, using aprogressive download protocol, or using any other protocol enabling thereceiver to begin playing the content as it is being delivered.

FIG. 3 illustrates one embodiment of a fractional-storage system.Assembling device group 661 g obtain erasure-coded fragments from theservers, such that the resulting outgoing bandwidth utilizations of eachserver in the array is 682 a to 682(N) correspondingly. FIG. 4illustrates a case where server 698 b has failed, its bandwidthcapability 682 b 1 is zero, and is therefore unable to provideerasure-coded fragments. The assembling devices from group 661 g, whichpreviously obtained fragments from server 698 b, may attempt to accessit again for additional fragments, but are now unable to get a response.These assembling devices therefore obtain fragments from alternativeservers. The end effect is that bandwidth 682 b is now loaded on thestill available servers, such that the total bandwidth 682 a 1 to682(N)1 approximately increases by a total amount equal to 682 b,optionally with no inter-server coordination, and simply by the factthat each assembling device selects alternative available servers forobtaining fragment on-the-fly. In one example, instead of obtaining fromserver 682 b 1, the assembling devices obtain from the least loadedavailable servers. In one embodiment, a control server selects thealternative server/s for the assembling devices. In one embodiment, theassembling devices use a fragment pull protocol to obtain the fragments,and approach the alternative servers. In one embodiment, the assemblingdevices use a push protocol to obtain the fragments, and approachalternative servers, possibly by obtaining multiple sub-transmissionscomprising fragment sequences. In this case, the sub-transmissions ofthe faulty server are discontinued and compensated for by othersub-transmissions from the alternative servers.

FIG. 5 illustrates an example similar to FIG. 4 with the difference thatservers 698 a, 698 b, and 698 c to 698(N) reside within, or get servicedvia, first, second, and third Internet backbone providers 300 j, 300 i,and 300 h correspondingly. The group of assembling devices 661 g isconnected to the Internet via network 300 k, which has access to allthree backbones, such that communication between the assembling devicesand servers 698 a to 698(N) pass via at least one of the backbones, ormore. If server 698 b is made unavailable to the assembling devices,optionally not due to a server failure, but rather due to congestion ora failure of the second Internet backbone provider 300 i, assemblingdevices 661 g compensate for the lost bandwidth by switching to theavailable servers on-the-fly. In one embodiment, networks 300 h, 300 i,and 300 j, are different physical sub-nets of one network connected tothe Internet. In one embodiment, the assembling devices are connected tonetworks 300 h, 300 i, and 300 j, via network 300 k, and then via one ormore Internet Exchange Points (“IX/IXP”).

In one embodiment, the assembling devices quickly react to the fault byapproaching other responsive servers. In one example, the assemblingdevices use a fragment pull protocol to retrieve alternative fragmentsfrom responsive servers within less than 5 seconds of the fault event,and approximately without affecting the ongoing streaming operation.

Referring again to FIG. 4, in one embodiment server 698 b fails and areplacement is needed. The replacing server (not illustrated) may storeeither the same erasure-coded fragments stored on server 698 b, or storeother unique erasure-coded fragments associated with the segments storedon 698 b. One method for regenerating the erasure-coded fragments storedon server 698 b, or generating equivalent unique erasure-codedfragments, includes the following steps: (i) identifying afailed/non-responsive server. (ii) determining the segmentscorresponding to the erasure-coded fragments that were stored on thenon-responsive server. This may be achieved either by a query to acontrol server, or by a query to servers in the distributed storage thatservice the same contents. (iii) reconstructing each segment whoseerasure-coded fragments are to be regenerated. This may be achieved byretrieving and decoding enough erasure-coded fragments. (iv) re-encodingat least the required erasure-coded fragments from the reconstructedsegments. The re-encoded fragments may be the same as the erasure-codedfragments previously stored on non-responsive server 698 b, or may benew, unique erasure-coded fragments. And (v) distributing the requirederasure-coded fragments to a new replacement server for 698 b.

FIG. 6A is a flow diagram illustrating one method for load-balancingfractional-storage servers, comprising the following steps: In step7220, retrieving, by an assembling device using a fragment pullprotocol, erasure-coded fragments associated with segments, from a setof fractional-storage servers. In step 7221, occasionally, whileretrieving the fragments, identifying at least one server from the setthat is loaded to a degree requiring replacement. And in step 7222,replacing, using the pull protocol, the identified server with asubstitute server that is not loaded to the degree requiringreplacement; wherein the substitute server and the remaining servers ofthe set are capable of delivering enough erasure-coded fragments neededin the course of reconstructing the segments. Optionally, the step ofidentifying at least one server from the set that is loaded to a degreerequiring replacement is based on receiving an indication that the atleast one server is loaded to a degree requiring replacement.Optionally, the method further comprising sending the indication, by theserver that is loaded to the degree requiring replacement, in responseto a fragment request or a load query. Optionally, the method furthercomprising measuring the latency between the assembling device and atleast one of the servers in the set, and identifying the at least oneserver that is loaded to a degree requiring replacement based on themeasured latency, whereby increased latency may suggest that the serveris loaded to a degree requiring replacement. Optionally, the methodfurther comprising measuring the variance in the latency in respondingto fragment requests, and identifying the at least one server that isloaded to a degree requiring replacement based on the latency variance,whereby increased latency variance may suggest that the server is loadedto a degree requiring replacement. Optionally, the method furthercomprising obtaining, from time to time, indications about servers, notin the set, which are not loaded to the degree requiring replacement;and selecting the substitute server using the obtained indications.Optionally, the substitute server is approximately the least loadedserver. Optionally, the identified server approximately does not haveenough unutilized bandwidth to support a fragment request. Optionally,the identified server approximately does not have enough processingresources available to support a fragment request. Optionally, theerasure-coding is rateless-coding potentially resulting in fragmentshaving a limitless redundancy factor, whereby high redundancy increasesthe number of servers from which the substitute server can be selected.

FIG. 6B is a flow diagram illustrating one method for load balancingfractional-storage servers, comprising the following steps: In step7230, retrieving, by assembling devices using a fragment pull protocol,erasure-coded fragments from a first set of fractional-storage servers.In step 7231, identifying a second set of servers that are able toincrease their current fragment delivery throughput. In step 7232,identifying, while retrieving the fragments, at least one server fromthe first set that is loaded beyond a certain threshold. And in step7233, replacing the server loaded beyond the certain threshold with aserver selected from the second set according to an algorithm.Optionally, the algorithm comprises random selection of the replacementserver. Optionally, the algorithm comprises selecting the least loadedserver as the replacement server. Optionally, the algorithm comprisesselecting the server having approximately the lowest latency in relationto the assembling device as the replacement server. Optionally, themethod further comprising obtaining data regarding the router hop-countbetween the assembling device and the servers, and deriving thelatencies from the hop-count data; whereby high hop-count indicates highlatency. Optionally, the method further comprising measuring thelatencies by the assembling device, and selecting the server havingapproximately the lowest latency variance in relation to the assemblingdevice as the replacement server. Optionally, the second set of serversare able to increase their current fragment delivery throughput by usingcurrently unutilized bandwidth. Optionally, the second set of serversare able to increase their current fragment delivery throughput by usingcurrently unutilized computational resources.

FIG. 7 illustrates a few examples of retrieving fragments according tolocality. In one example, the fractional-storage servers are connectedto a data network or networks comprising the routers 201 to 209.Assembling devices 235, 237, and 238 are connected to the same datanetwork or networks, and K=3, meaning that any assembling device needsto obtain 3 erasure-coded fragments per segment from optionally 3different servers out of the 10 in order to successfully reconstruct thesegment.

Each assembling device tries to obtain erasure-coded fragments fromfractional-storage servers that are closest to it topologically. In oneembodiment, the topological distance is a function of the number ofseparating routers. Assembling device 238 can select three servers fromgroups 242, 248 or 249. According to the minimal path criterion, itretrieves the erasure-coded fragments from servers 399 h to 399 i ofgroup 248, since they are only one router 208 away. Groups 242 and 249are three (208, 202, 203) and five (208, 202, 203, 201, 209) routersaway, and are therefore not selected for retrieval. Similarly, device237 selects three servers out of group 242, and device 235 can selectany three servers from groups 242 and 249, since both are located fourrouters away.

In one embodiment, if topologically close servers do not respond to theassembling device, or report a bandwidth limitation, the assemblingdevice will attempt to obtain an erasure-coded fragment from the nexttopologically closest server.

In one embodiment, an assembling device attempts to obtain erasure-codedfragments from servers featuring the lowest latency. Upon no response,for whatever reason, the assembling device will attempt to retrieve fromthe next lowest latency server. In one embodiment, the assembling deviceobtains information regarding the unutilized fragment deliverybandwidths of servers, and then attempts to retrieve from the lowestlatency servers out of the servers having enough unutilized bandwidth.In one embodiment, the assembling device obtains information regardingthe unutilized fragment delivery bandwidths of the servers, and thenattempts to retrieve from the topologically closest servers out of theservers having enough unutilized bandwidth.

Still referring to FIG. 7, in one embodiment the assembling devicesselect servers according to a latency criterion, such as selectingservers with the shortest time between fragment request and fragmentdelivery, or selecting servers having latency below a dynamic or staticthreshold. Assembling device 237 assembles content from servers 399 c,399 f, 399 g, and assembling device 235 assembles content from servers399 b, 399 c, 399 g (both use a mixture of servers from groups 242 and249). At a certain point in time, router 209 becomes congested orblocked, and prevents the erasure-coded fragments from servers 399 b and399 c from arriving at assembling devices 235 and 237, or causes thefragments to arrive with an increased delay. Therefore, assemblingdevice 235 switches to three servers of group 242, and assembling device237 switches from server 399 c to server 399 e.

In one embodiment, the assembling device selects fractional-storageservers according to the following criterion: first, servers withadequate unutilized fragment delivery bandwidth are considered, then outof these, those with latency below a threshold are considered, and outof these, the servers with minimal topological routing path areselected.

In some embodiments, the assembling devices use a fragment pull protocolto retrieve the fragments, and approach servers having low latency orlow hop count as compared to other servers. In some embodiments, theassembling devices use a push protocol to retrieve the fragments, andapproach servers having low latency or low hop count as compared toother servers, optionally by obtaining multiple sub-transmissionscomprising fragment sequences.

In one embodiment, a plurality of unsynchronized retrieving assemblingdevices, which optionally use fragment pull protocol, choose the leastloaded servers from which to retrieve the erasure-coded fragments.Optionally, the servers have almost no inter-communication between themand the load balancing calculation is performed by the retrievingassembling devices. Because the assembling devices can select the leastloaded servers, the assembling devices manage the load balancing. Whenthe erasure-coded fragments stored by the servers are uniqueerasure-coded fragments, the retrieving assembling device may retrieveerasure-coded fragments from any relevant server. Therefore, it may beenough for the retrieving assembling device to have indication of theload on its targeted servers, and retrieve enough erasure-codedfragments from the least loaded servers.

In one embodiment, a server signals the retrieving assembling devicethat it is close to its bandwidth limit and the assembling devicesearches for an alternative server. Optionally, the assembling deviceselects the server according to one or more of the following parameters:locality, cost, latency, or reliability. In one embodiment, the serversregister their loads on a central server, and the assembling deviceselects the server to retrieve from, from the registered servers. In oneembodiment, a central server, holding the loads of the various servers,determines for the assembling devices from which server to retrieve theerasure-coded fragments.

In one embodiment, assembling devices measure the latency of thedifferent servers in responding to fragment requests, and then use thelatency information to estimate the loads on the servers. In oneexample, a high latency may indicate a high load on the server.

In one embodiment, the topological router hop count between anassembling device and fragment delivering servers is used to estimatethe latency of the servers in responding to fragment requests.

In one embodiment, the latency of fragment delivering servers inresponding to fragment requests by an assembling device is used toestimate the topological router hop count between an assembling deviceand the servers.

In one embodiment, the assembling devices perform several latencymeasurements for the different servers in responding to fragmentrequests, and then use the latency variance information to estimate theloads on the servers. In one example, a high latency variance maysuggest a high load on server.

In one embodiment, fractional-storage servers, from which the fragmentsare obtained for reconstructing a segment, are selected based on anapproximately random selection algorithm from all of the servers storingthe relevant fragments. In one example, an approximately randomselection algorithm weighted according to the unutilized bandwidth ofthe servers is used for the approximately random selection of servers.The weighted random selection algorithm assigns servers with selectionprobabilities proportional to the amount of unutilized bandwidth forfragment delivery in each of the servers, such that the probability toselect a server having a larger amount of unutilized bandwidth is higherthan the probability to select a server having a lower amount ofunutilized bandwidth.

The following embodiments describe processes for on-the-fly selectionand re-selection of fractional-storage servers from which to obtainerasure-coded fragments.

In one embodiment, a method for selecting enough new servers from whichto obtain fragments, based on the unutilized bandwidth of the servers,includes the following steps: (i) accessing data regarding serversstoring relevant fragments (referred to as the relevant servers); (ii)accessing data regarding the unutilized bandwidth of the relevantservers. Optionally, the data is received by the assembling device fromthe relevant servers; and (iii) obtaining fragments from enough of therelevant servers having approximately the highest unutilized bandwidth;or obtaining fragments from enough of the relevant servers selectedrandomly and having unutilized bandwidth above a certain threshold.

In one embodiment, a method for selecting enough new servers from whichto obtain fragments, based on latency, includes the following steps: (i)accessing data regarding the relevant servers; (ii) accessing dataregarding the latencies from the relevant servers to the assemblingdevice; and (iii) obtaining fragments from enough of the relevantservers having the lowest latencies; or obtaining fragments from enoughof the relevant servers selected randomly and having latencies below acertain threshold.

In one embodiment, a method for selecting enough new servers from whichto obtain fragments, based on bandwidth and latency, includes thefollowing steps: (i) accessing data regarding the relevant servers; (ii)accessing data regarding the unutilized bandwidth of the relevantservers; (iii) identifying more than enough relevant servers having themost unutilized bandwidth; or randomly identifying more than enoughrelevant servers having unutilized bandwidth above a certain threshold;(iv) accessing data regarding the latencies from the identified serversto the assembling device; and (v) obtaining fragments from enough of theidentified servers having the lowest latencies; or obtaining fragmentsfrom enough of the relevant servers selected randomly and havinglatencies below a certain threshold.

In one embodiment, a method for selecting enough new servers from whichto obtain fragments, based on latency and bandwidth, includes thefollowing steps: (i) accessing data regarding the relevant servers; (ii)identifying more than enough relevant servers having latencies to theassembling device below a certain threshold; or randomly identifyingmore than enough relevant servers having latencies to the assemblingdevice below a certain threshold; (iii) accessing data regarding theunutilized bandwidth of the identified servers; and (iv) obtainingfragments from enough of the identified servers having the highestunutilized bandwidth; or obtaining fragments from enough of the relevantservers selected randomly and having the highest unutilized bandwidth.

In one embodiment, a method for selecting enough new servers from whichto obtain fragments, based on locality, includes the following steps:(i) accessing data regarding the relevant servers; (ii) accessing dataregarding the network topology distance (locality) from the relevantservers to the assembling device; and (iii) obtaining fragments fromenough of the topologically closest relevant servers; or obtainingfragments from enough of the relevant servers that are located in thesame sub-network as the assembling device, or located in the closestsub-networks.

In one embodiment, a method for selecting enough new servers from whichto obtain fragments, based on bandwidth and locality, includes thefollowing steps: (i) accessing data regarding the relevant servers; (ii)accessing data regarding the unutilized bandwidth of the relevantservers; (iii) identifying more than enough relevant servers having themost unutilized bandwidth; or randomly identifying more than enoughrelevant servers having unutilized bandwidth above a certain threshold;(iv) accessing data regarding the network topology distance from therelevant servers to the assembling device; and (v) obtaining fragmentsfrom enough of the topologically closest relevant servers; or obtainingfragments from enough of the relevant servers that are located in thesame sub-network as the assembling device, or located in the closestsub-networks.

In one embodiment, a method for selecting enough new servers from whichto obtain fragments, based on latency and locality, includes thefollowing steps: (i) accessing data regarding the relevant servers; (ii)identifying more than enough relevant servers having latencies to theassembling device below a certain threshold; or randomly identifyingmore than enough relevant servers having latencies to the assemblingdevice below a certain threshold; (iii) accessing data regarding thenetwork topology distance from the relevant servers to the assemblingdevice; and (iv) obtaining fragments from enough of the topologicallyclosest relevant servers; or obtaining fragments from enough of therelevant servers that are located in the same sub-network as theassembling device, or located in the closest sub-networks.

In one embodiment, a method for selecting enough new servers from whichto obtain fragments is based on bandwidth, latency, locality, and,optionally, one or more additional relevant parameters. The method mayweigh the different parameters in various ways, all of them are intendedto be covered by the embodiments. For example, the method may includethe following steps: (i) accessing data regarding the relevant servers;(ii) receiving data regarding the unutilized bandwidth latencies to theassembling device, and topology distances to the assembling device;(iii) weighting the received data and identifying a quantity of the mostproper relevant servers, which can provide enough fragments toreconstruct content; and (iv) obtaining the fragments from theidentified servers. In another example, the method may include thefollowing steps: (i) accessing data regarding the relevant servers; (ii)identifying a set of more than enough relevant servers having the mostunutilized bandwidth; or randomly identifying a set of more than enoughrelevant servers having unutilized bandwidth above a certain threshold;(iii) from the set, identifying a sub-set of more than enough relevantservers having latencies to the assembling device below a certainthreshold; or randomly identifying more than enough relevant servershaving latencies to the assembling device below a certain threshold; and(iv) obtaining fragments from enough of the topologically closestrelevant servers out of the sub-set; or obtaining fragments from enoughof the relevant servers out of the sub-sets, which are located in thesame sub-network as the assembling device, or located in the closestsub-networks.

In one embodiment, a server may be loaded to a point that it isapproximately unable to transmit additional fragments as a response tonew fragment requests or new sub-transmission requests. The server mayalso be too loaded to continue transmitting fragments to its currentlyserved assembling devices. In one example, these cases result from oneor more of the following conditions: (i) server hardware limitation,such as CPU power or memory bus constraints, which prevents it fromdelivering fragments beyond a certain throughput, (ii) outgoingcommunication link limitation, such as a fixed-bandwidth line, whichprevents the server from transmitting fragments beyond a rate that canbe supported by the line, (iii) sharing of an outgoing communicationline with other servers, and the other servers utilizing the shared lineto a point that lowers the bandwidth available for fragmenttransmission, and (iv) sharing the fragment storage and transmissionsoftware together with other applications on one physical server, andthe other applications consuming CPU, memory, or communication resourcesto a point that affects the ability of the fragment storage andtransmission software to respond to fragment or sub-transmissionrequests.

In the claims, a sentence such as “erasure-coded fragments encoded witha redundancy factor R>1 and associated with segments of streamingcontents” is to be interpreted as erasure-coded fragments encoded withone redundancy factor or with a plurality of redundancy factors greaterthan one. For example, some fragments associated with a first set ofsegments of content may have a redundancy factor of two, and somefragments associated with a second set of segments of the same contentmay have a redundancy factor of three.

In some embodiments, approximately random selection offractional-storage servers is utilized for dealing with changes innetwork conditions, such as packets loss and/or server failure, withoutaffecting the user experience, and optionally without prior knowledge ofthe type of the change in network condition. Optionally, newerasure-coded fragments are requested from the randomly selected serversinstead of failed requests. Optionally, failed servers are replaced withother servers. Optionally, the combination and/or the number offractional-storage servers from which the fragments are obtained changesover time. Optionally, the number of redundant fragment requests changesover time.

In one example, a constant packet loss condition causes a constantfragment loss condition, which means that a certain percentage offragments fail to be obtained by the assembling device. In this case, anapproximately random selection of new servers may solve the problem, notnecessarily because of the randomness of the selection (a generalfragment loss condition may affect all servers), but simply because itgenerates more fragment requests to compensate for the loss, resultingin an increased fragment-delivery throughput that approximately levelsat an average steady state value of: (NominalThroughput/(1−Fragment_Loss_Ratio)), wherein the Nominal Throughput isthe fragment-delivery throughput resulting when no packets are lost, andthe Fragment_Loss_Ratio is the (fragment_lost/fragments_sent) ratio,which is a parameter that increases monotonically with the packet-loss.In another example, the failure is specific to one or more servers, andthe approximately random selection of new servers finds new servershaving lower failure ratios. In this case, the random selection solvesthe problem, since trying to retrieve again from problematic servers mayhave no positive effect. The above two examples demonstrate how a singleselection strategy successfully copes with different types of failures,while resulting in a different behavior according to the type of failure(different resulting fragment delivery rates for example), and all thatwithout prior knowledge of the exact nature of the failure. In anotherexample, the servers are deployed over multiple networks and thecommunication fault comprises a failure of one of the networks causingrelated servers to be inaccessible. As a solution, the assembling deviceapproximately randomly reselects the servers until it communicates withenough accessible servers to reconstruct a segment. Other examples arepossible, in which an unknown failure is correctly handled byapproximately random on-the-fly server selection.

In one embodiment, different servers receive different weightsproportional to their bandwidth. For example, the higher the bandwidthcapability of the server, the higher the server coefficient; the higherthe server coefficient, the higher the probability of selecting theserver by an assembling device. In one embodiment, selecting the serversapproximately randomly enables the fractional-storage system to operatewell when the assembling devices do not know the load on at least someof the servers.

In one embodiment, the approximately random selection of serversproduces a set of source servers from which erasure-coded fragments areretrieved using a fragment pull protocol. In another embodiment, theapproximately random selection of servers produces a set of sourceservers from which erasure-coded fragments are retrieved using apush-protocol. In this case, multiple sub-transmissions may be used totransport the fragments from multiple servers to an assembling device.When new server sources are randomly selected instead of others, theassembling device may end the sub-transmissions associated with thereplaced servers, and initiate new sub-transmissions from the replacingservers, optionally from the point that the terminated sub-transmissionswere interrupted.

In one embodiment, the approximately random server selections are madefrom the servers not currently servicing the assembling device. In oneembodiment, the approximately random server selections are made from allservers storing relevant fragments, including the server(s) thatserviced the assembling device before being identified as problematic.

In one embodiment, approximately random reselections of servers areperformed occasionally, even if all currently servicing servers arefunctioning correctly. In this case, the assembling device may select afew servers from the current set, to be randomly replaced. In oneembodiment, functioning servers are kept throughout several segmentretrieval cycles, and potentially for the entire delivery cycle of asegmented content.

In one embodiment, the assembling device does not know which of theservers store erasure-coded fragments related to the content to beretrieved, but the assembling device does know over how many servers(from the total number) the erasure-coded fragments are distributed.Therefore, the assembling device compensates for the infertile requestsby increasing the number of requests for erasure-coded fragments.Optionally, the requested servers are selected based on approximatelyrandom algorithm.

In one embodiment, a method for reselecting one or morefractional-storage CDN servers on-the-fly, comprising: pullingerasure-coded fragments from the servers; estimating the servers' load,latency, network congestion, and packet loss; and operating a fuzzyalgorithm on the estimations in order to replace at least one of theservers with at least one other fractional-storage server. Optionally,the method further comprising operating the fuzzy algorithm based onmeasurements of many assembling devices and recommendations receivedfrom a central server. Optionally, the method further comprisingreplacing the servers quickly after missing a fragment. And optionally,the fuzzy algorithm weighs many possible solutions and converges to asufficient one.

FIG. 8 illustrates one embodiment of a fractional-storage system storingerasure-coded fragments. Content 100, which may optionally be streamingcontent, is segmented into content segments 101 a, 101 b to 101 j (forbrevity referred to as segments). Each of the segments is encoded intoerasure-coded fragments. For example, segment 101 a is encoded intoerasure-coded fragments 390 a to 390(N). The erasure-coded fragments aredistributed to the fractional-storage servers 399 a to 399(N) and/or tothe bandwidth amplification devices 610 aa. The erasure-coded fragmentsare then obtained by assembling devices like 661 or proxy servers likeproxy server 661 s from the fractional-storage servers 399 a to 399(N)and/or the bandwidth amplification devices 610 aa. The obtainederasure-coded fragments are decoded to reconstruct the segments. Theproxy server 661 s may broadcast/multicast and/or re-stream thereconstructed content, optionally using standard streaming technique, toits client(s) 6610, optionally over network 300 n. In some embodiments,the content distribution is performed in real time. In some embodiments,the content assembly is performed in real time and the presentationstarts a short time after the content request.

Similarly to content 100, additional contents are segmented, encodedinto erasure-coded fragments, and distributed to the fractional-storageservers and/or to the bandwidth amplification devices. Each segment maybe reconstructed independently of other segments by obtaining anddecoding enough erasure-coded fragments generated from that segment.

In some embodiments, the encoding scheme is erasure codes and/orrateless codes. In some embodiments, the fractional-storage servers 399a to 399(N) are Content Delivery Network (CDN) servers, optionallyaccessed over the public Internet. In some embodiments, the control,management, content reception, content segmentation, segment encoding,erasure-coded fragment distribution, allocation of bandwidthamplification devices, and/or other kind of central supervision andoperation may be performed by managing server(s) 393, which may be apart of the CDN network. It is noted that the term “fractional-storageserver” is not limited to a large server and, according to the context,may include a fractional-storage bandwidth amplification device, afractional-storage peer server, or other types of fractional-storageservers.

In one embodiment, different quantities of erasure-coded fragments aregenerated per different segments. In one embodiment, some segments storedata that is considered more important than data stored in othersegments, and relatively more erasure-coded fragments are generated fromthe segments storing the more important data than from the segmentsstoring the less important data.

In some embodiments, the content is segmented into a plurality ofsegments to enable beginning to play the content as it is beingobtained, and optionally enable trick play. The different segments mayor may not be of the same size.

In one example, the content supports streaming presentation, and thesegments are small enough to enable presentation shortly after beginningthe reception of the first segment(s). For example, each segment mayinclude 96 KByte, allowing a 5 Mbps receiver to download the segment inapproximately 0.2 seconds, and optionally begin the presentation shortlythereafter. In one embodiment, the time to play is reduced by segmentingcertain portions of the content into smaller segments, while theremaining portions are segmented into larger segments. A smaller segmentcan be retrieved faster, while a larger segment may be better optimizedfor storage gain and/or efficient transmission.

The term “redundancy factor” as used herein denotes the following ratio:(total size of the unique erasure-coded fragments generated from asegment and actually stored on the servers)/(size of the segment).

Assuming all segments have approximately the same size and all fragmentsgenerated from the segments have approximately the same size (withoutlimiting any of the embodiments), the term “storage gain” as used hereindenotes the following ratio: (size of a segment)/(size of anerasure-coded fragment). If the server stores more than oneerasure-coded fragment per segment, the storage gain denotes thefollowing ratio: (size of segment)/((size of erasure-codedfragment)*(number of stored erasure-coded fragments per segment)).

In one embodiment, the short segments are 96 Kbytes in size, and thelong segments are 960 Kbytes in size. The redundancy factors used forencoding short and long segments into fragments are 100 and 5respectively. 1500 Bytes fragments are used for both sizes. The shortsegments are therefore encoded into (96K/1500)×100=6,400 fragments, fromwhich only about 64 are needed for reconstruction, and the long segmentsare encoded into (960K/1500)×5=3,200 fragments, from which only about640 are needed for reconstruction. Short segments are reconstructed morequickly than long ones, as they require fewer fragments to be decoded.Optionally, each fragment is stored on a different server, resulting ina storage gain of 64 for short segments, and 640 for long segments.

The following embodiments discuss different methods for segmenting thecontent. In one embodiment, at least one portion of the content issegmented into multiple segments in sizes within a first size range, andthe remainder of the content is segmented into a plurality of segmentsin sizes within a second size range (additional size/s may be addedsimilarly). The sizes included in the second size are larger than thesizes included in the first size range. Pluralities of erasure-codedfragments are generated from each of the segments. The segments of sizeswithin the first size range are better suited for fast retrieval, andthe segments of sizes within the second size range are better suited forhigh-gain storage. In one example, the segments in sizes within thefirst size range belong to approximately the beginning of the content.In one example, the segments in sizes within the first size range belongto locations within the content requiring trick play access. In oneembodiment, the segments of the first type are encoded into fewerfragments than the segments of the second type. This allows a fastretrieval of the shorter segments.

In one example, the content 100 is a 1 GByte encoded H.264 file, storinga 2-hour motion picture, and is segmented into approximately 10,000segments of approximately 100 Kbytes each. In another example, thecontent 100 is a 4 MByte web-site information (HTML, FLASH, or any othercombination of information that encodes the presentation of a website),and is segmented into 4 segments of approximately 1 MByte each.

FIG. 9 illustrates one example in which the content 100 is segmentedinto segments, such that the first segment 104 a is smaller than theconsecutive segment 104 b, which is smaller than following segments 104c and 104 d. In another example, the content 100 is segmented intosegments, such that the first several segments (e.g. 104 aa and 104 bb,which are the same size), are smaller than consecutive segments (e.g.104 cc and 104 dd, which are the same size).

FIG. 10 illustrates one example in which the content 100 is segmentedinto cyclic sets of successive segments increasing in size. For example,105 b is equal or larger in size than 105 a, and so on, up to segment105 d; 105 f is equal or larger in size than 105 e, and so on, up tosegment 105 h. In one example, segment 105 e is equal in size to segment105 a. Point 105EP represents the ending of the first set, and thebeginning of the second set.

In one embodiment, segments are created on-the-fly, such as during alive event or when the content is made available to the segmentationprocess as an on-going stream. In one embodiment, the content supportsstreaming presentation, and the segments are of the small size, toenable content presentation shortly after beginning the reception of thefirst segment (or any other segment). In addition, the erasure-codedfragments are kept as small as possible, while still enabling efficienttransport over an IP network. For example, each erasure-coded fragmentis about 1500 Bytes and can be transported using one IP packet.

It is to be noted that streaming content may also be manifested as anintermediate product of a process. For example, in a case where a videocamera outputs erasure-coded fragments that can be decoded intostreaming content, the intermediate data from which the erasure-codedfragments are generated is considered to be streaming content (even ifthe video camera does not output that intermediate data). Moreover,streaming content may include: content that is produced and thenimmediately transmitted to a receiving server, content that is producedbut stored for any length of time before being transmitted to areceiving server, content that is transmitted to a receiving server andthen immediately sent from the receiving server to a client, contentthat is transmitted to a receiving server, then buffered for some timeat the receiving server and then sent from the receiving server to aclient, content that is solely played at a client, and content that ismanipulated or changed or reacted to at the client while a continuationof the content is still being played at the client.

FIG. 11 (without the fragments marked with dashed lines) illustrates oneexample of distributing the erasure-coded fragments to ‘M’ CDN servers399 a to 399(M), connected to a network 300. Encoded fragments 310 a to310(M) of a first segment are sent for storage in servers 399 a to399(M) respectively. Similarly, erasure-coded fragments 320 a to 320(M)of a second segment are sent for storage in servers 399 a to 399(M)respectively. In addition, other erasure-coded fragments associated withother segments of other contents, illustrated as erasure-coded fragments390 a to 390(M), are sent for storage in servers 399 a to 399(M)respectively. The number of unique erasure-coded fragments from eachsegment that are stored on the servers (399 a to 399(M)) is equal to Min this example, where M may be smaller than the maximum number ofunique erasure-coded fragments, meaning that only a subset of thepotential erasure-coded fragments are actually stored. It is alsopossible to store the maximum number of unique erasure-coded fragments,or store more than one unique erasure-coded fragment per segment perserver. The network 300 may be the Internet for example, or any otherdata network connecting multiple nodes, such as a private IP network, ora Wide Area Network (“WAN”). In one embodiment, the fragments markedwith dashed lines illustrate one example where (N-M) additional serversare added to the array, and (N-M) new unique erasure-coded fragments persegment per content (310(M+1) to 310(N), 320(M+1) to 320(N), and390(M+1) to 390(N)) are generated and added to the array. In oneembodiment, only M out of the maximum possible erasure-coded fragments(L) are actually generated for storage in the first place. In oneembodiment, when the additional N-M erasure-coded fragments are neededfor storage (e.g., when additional servers are made available), theremainder of the N-M erasure-coded fragments are actually generated. Anytime that additional unique erasure-coded fragments are needed, thisprocess of calculating the additional erasure-coded fragments isrepeated, up to the point that all L possible erasure-coded fragmentsare used.

In one embodiment, and especially when using rateless coding, L may bechosen as a sufficiently large number to account for any realisticfuture growth of the server array. For example, a segment of 96 Kbytesis expanded using a rateless code with a ratio of 1 to 2̂16 originalsymbols to encoded data, into an encoding symbol of potential size 6.29GBytes. Assuming a 1500 Bytes erasure-coded fragment size, thenpotentially 4.19 million unique erasure-coded fragments can begenerated. Now, it is safe to assume that for all practical uses, theserver array will not grow to more than 4.19 million nodes, and maycontain several thousands of servers, meaning that the encoded data canbe used in all cases where additional unique erasure-coded fragments areneeded, by generating new erasure-coded fragments out of the segment.Optionally, a server may store erasure-coded fragments for only some ofthe segments.

In one example of redundancy factor and storage gain (without thefragments marked with dashed lines), server 399 a stores onlyerasure-coded fragment 310 a from a first segment, erasure-codedfragment 320 a from a second segment, and erasure-coded fragment 390 afrom a third segment. Assuming that: (i) the segment size is 1024Kbytes; (ii) the segment is encoded using erasure code into a 4096 KByteencoded segment; (iii) the encoded segment is segmented into 256erasure-coded fragments of size 4096/256=16 KByte; and (iv) theerasure-coded fragments are stored on 256 servers (M=256); it turns outthat each server stores only a 1/64 portion of the original size of thesegment. This means that each server can manage with only 1/64 of thestorage requirements in comparison to a situation where it had to storethe entire segment. In addition, there are 256 erasure-coded fragmentsaltogether from each encoded segment, meaning that an assembling devicethat is assembling the erasure-coded fragments from the servers needonly select slightly more than 64 erasure-coded fragments in order tocompletely reconstruct the segment, and it can select whichever slightlymore than 64 erasure-coded fragments it desires out of the 256 possiblyavailable. The redundancy factor in this example is approximately256/64=4. All contents in this example enjoy a factor of 64 in storagegains, meaning that server 399 a, for example, stores only 1/64 of theinformation associated with the first segments and any additionalsegments belonging to other contents. In one example, each serversupports high volume storage of between about 500 GByte and 500 TBytes,optionally utilizing hard drive, Solid State Drive, or any other highvolume storage device(s). In these cases, each server may store manymillions of erasure-coded fragments, associated with millions ofsegments, belonging to hundreds of thousands of different contents, andpossibly more.

In one embodiment, new content initially encoded with a low redundancyfactor is distributed to an initial number of fractional-storageservers. As the content is distributed to more servers, additionalunique fragments are encoded and therefore the redundancy factorincreases. Optionally, as the content's popularity increases, and/or asthe load on the fractional-storage servers increases, the redundancyfactor is increased, and vice versa.

In one embodiment, multiple unique erasure-coded fragments per segmentof a new content are distributed to an initial number offractional-storage servers with a low storage gain (i.e. each serverstores multiple unique erasure-coded fragments per encoded segment). Asthe content is distributed to more fractional-storage servers, some ofthe erasure-coded fragments stored on the initial number offractional-storage servers are removed and thereby the storage gain isincreased. Optionally, as the demand for the content increases, thestorage gain is decreased, and vice versa.

FIG. 12 illustrates three examples (each depicted by one of the columnsA-C) of changing the redundancy factor according to the demand. Column Aillustrates one simplified example of a storage array including 16servers (1001 to 1016). Each server stores up to 2 differenterasure-coded fragments, and can service an erasure-coded fragmenttransmission bandwidth of up to B. Assuming three contents (#1, #2, and#3) processed to segments and erasure-coded fragments with a storagegain of 4.

Assuming content #1 is the most popular, and requires a peak bandwidthof 11×B. Since each server can service up to bandwidth B, at least 11servers are needed to service content #1 bandwidth requirements. Content#1 is therefore encoded into 11 unique erasure-coded fragments persegment, illustrated as group g1 of erasure-coded fragments stored onservers 1001 to 1011. Out of these 11 erasure-coded fragments, it issufficient to obtain slightly more than 4 erasure-coded fragments inorder to reconstruct a segment of content #1. Therefore, the resultingredundancy factor of the stored fragments associated with content #1 isapproximately 11/4=2.75. Content #2 requires less bandwidth, and manageswith a peak of 7×B. It is therefore encoded into 7 unique erasure-codedfragments per segment, illustrated as group g2 of erasure-codedfragments on servers 1010 to 1016. Therefore, the redundancy factor ofthe stored fragments associated with content #2 is 7/4=1.75. Content #3requires a peak bandwidth of 5×B, but for some reason (for example,being a more critical content), it is encoded into 14 erasure-codedfragments per segment, illustrated as group g3 of erasure-codedfragments on servers 1001 to 1009 and 1012 to 1016. Therefore, theredundancy factor of the stored fragments associated with content #3 is14/4=3.5. This concludes the storage availability of the servers in thisexample, as every server stores two erasure-coded fragments.

Column B illustrates an example where content #2 becomes more popularthan content #1, and therefore requires more bandwidth and hence more ofa redundancy factor. This is achieved by eliminating 5 erasure-codedfragments associated with content #1 that were previously stored onservers 1001 to 1005, and replacing them with 5 new unique erasure-codedfragments g4 associated with content #2. This brings the total number oferasure-coded fragments per segments of content #1 and #2 to 6 and 12respectively. In column C, new content #4 is stored on servers 1001 to1003 and 1014 to 1016 (illustrated as g5), by eliminating 3erasure-coded fragments of content #1 and 3 erasure-coded fragments ofcontent #2.

Throughout the examples of FIG. 12, a record of “what erasure-codedfragments are stored where” may be: (i) kept in each of the servers 1001to 1016. In this case, when an assembling device is assembling content#2, it will send a query to servers 1001 to 1016, asking which one isstoring erasure-coded fragments of content #2; (ii) kept in a controlserver. In this case, an assembling device will ask the control serverto send back a list of all servers storing erasure-coded fragments ofits required content.

In one embodiment, the fractional-storage system is approximatelyinsensitive to the mixture of the consumed contents as long as theaggregated throughput is below the total throughput of thefractional-storage servers.

FIG. 13 illustrates one example of a fractional-storage server array,including N servers (399 a to 399(N)), and storing content A, whichincludes erasure-coded fragments 310 a to 310(N), and content B, whichincludes erasure-coded fragments 320 a to 320(N). Each server isconnected to the network 300 with a fragment delivery bandwidthcapability B 339. Therefore, the N servers have an aggregated bandwidthof B×N. A first group of assembling devices 329 a consumes content A atan average bandwidth Ba 349 a. A second group of assembling devices 329b consumes content B at an average bandwidth Bb 349 b. Since all of theservers participate in the transmission of the two contents, the firstand second groups can potentially consume all server bandwidth, up tothe limit where Ba+Bb=N×B, with any ratio of demand between the firstand second contents, and with no special provisions to be made whenstoring the erasure-coded fragments related to the two contents in thefractional-storage server array.

FIG. 14 illustrates the case where the first group 328 a, which consumescontent A, becomes larger than 329 a, with a larger bandwidth Ba 348 a.The second group 328 b, which consumes content B, becomes smaller than329 b, with a smaller bandwidth Bb 348 b, such that Ba is about the sameas Bb. In this case, the array can still be exploited up to theaggregated bandwidth, since, as before, Ba+Bb can still be almost ashigh as N×B. FIG. 15 illustrates the case where the first group hasdisappeared, allowing the second group 327 b, which consumes content B,to extract an aggregated bandwidth of Bb 347 b that can potentiallyreach the limits of the server array, such that Bb=N×B. Again, this isachieved without updating the erasure-coded fragments associated withcontent A and content B, and without using inter-server interaction.

In some embodiments, the ability to utilize the aggregated bandwidth ofapproximately all of the participating servers, for the delivery ofabout any mixture of contents with about any mixture of contentbandwidth demand, is made possible by one or more of the following: (i)each assembling device selecting a subgroup of the least loadedfractional-storage servers from which to retrieve the necessary numberof erasure-coded fragments to reconstruct a segment or several segments(least-loaded server selection criterion); or (ii) each assemblingdevice approximately randomly selecting a subgroup from which toreconstruct a segment or several segments, such that when manyassembling devices select at random, the various fractional-storageservers are selected approximately the same number of times (or inproportion to their available resources, such as unutilized bandwidth),which in turn balances the load between the participating servers(random server selection criterion). It is noted that (i) the selectionsmay be made by either the assembling devices themselves, or may be madefor the assembling devices by a control server, which then communicatesthe selections to each of the assembling devices; (ii) the selectionsmay be made approximately for each segment, or for a group of segments,or only once per content at the beginning of the content; (iii) someassembling devices may use an approximately random server selectioncriterion, while other assembling devices may use least-loaded serverselection criterion; (iv) the least-loaded selected servers may beselected out of a portion of all available fractional-storage servers.For example, the least-loaded servers may be selected fromfractional-storage servers with low latency response or with low hopcount to the assembling device; (v) the least-loaded servers may includeservers having the most unutilized bandwidth. Additionally oralternatively, it may include servers having any unutilized bandwidthleft to serve additional assembling devices; (vi) an approximatelyrandom or least-loaded selection of servers may be made such that allservers are selected to determine a subgroup, or it can be made suchthat every time selections are made, only some servers are selected,while the others remain as before. In these cases, the assembling deviceruns a process in which only a small portion of the servers currently inthe serving subgroup are reselected. In the case of approximately randomselection, the assembling device may randomly select the number ofservers in the serving subgroup for random selection (reselection inthis case, since they are replacing other servers already in the servingsubgroup of the specific assembling device), such that eventually, overtime, all servers within the serving subgroup have the chance to berandomly reselected. In the case of least-loaded server selection, onlythe most loaded servers within the serving subgroup may be selected andreplaced by less-loaded servers.

In some embodiments, a broadcast-like effect is achieved by distributingto and retrieving from fractional-storage servers a broadcastchannel/live content in real time, using a combination of real timedistribution and real time retrieval techniques. In a broadcast-likeeffect, a given channel or content for broadcasting is distributed to atleast one assembling device, optionally by means of pushing relevantfragments to the assembling device, or by pulling the relevant fragmentsby the assembling device, and potentially to many assembling devices atapproximately the same time, which creates a similar effect totraditional broadcasting.

FIG. 16 illustrates one embodiment of using the entire aggregatedbandwidth of the fractional-storage servers for delivering multiplecontents. Approximately any number of contents having any mixture ofbandwidth demand per content may be delivered, as long as the aggregatedbandwidth demand does not exceed the aggregated bandwidth of thefractional-storage servers. In one example, broadcast-like streams 3101,3102, and 3103 are delivered to multiple assembling devices via multiplefractional-storage servers. Each stream is a live TV channel carryingmultiple TV programs. For example, stream 3101 comprises TV programs3110 to 3112, each spanning a specific time interval. The other streamscomprise of multiple TV programs as well. Before time T1, stream 3130has a bandwidth demand of 3130′ (meaning that all assembling devicesthat are currently retrieving stream 3130′ use a total bandwidth of3130′ out of the fractional-storage servers). The other streams 3120 and3110 have bandwidth demands of 3120′ and 3110′ respectively. The totalbandwidth demand of the three streams 3130′+3120′+3110′ does not exceedthe aggregated bandwidth of the fractional-storage servers 3150, andtherefore all streams are fully delivered to the assembling devices. Theload of the three streams is spread approximately equally among theparticipating fractional-storage servers, optionally because of amechanism that selects the least-loaded servers to serve each assemblingdevice, and/or a mechanism that approximately randomly selects serversto serve each assembling device. At time T1, TV program 3120 ends, andTV program 3121 starts. Program 3121's demand 3121′ is higher than theprevious demand 3120′, and therefore a higher aggregated bandwidth isdrawn from the fractional-storage servers. Still, the aggregatedbandwidth demand of all three streams (3130′+3121′+3110′) is lower thanthe maximum possible 3150, and therefore the newly added bandwidthdemand is fully supported by the servers. Optionally, the additionaldemand created by TV program 3121 (3121′ minus 3120′) is caused by theaddition of new assembling devices that join stream 3102 and retrievingadditional erasure-coded fragments. Additionally or alternatively, theadditional demand created by TV program 3121 is caused by a higherbandwidth demand of TV program 3121, such as 3D data or higherresolution. Newly added assembling devices may choose fractional-storageservers from which to retrieve, according to a least-loaded serverselection criterion and/or an approximately random server selectioncriterion, and therefore the total load is still spread approximatelyequally among the participating servers. At time T2, TV program 3110ends, and a new program 3111 begins, which is less popular, andtherefore creates a lower bandwidth demand 3111′. The result is adecrease in the total delivered bandwidth. At time T3 TV program 3130ends, and TV program 3131 starts with a higher bandwidth demand of3131′. At time T4 both TV programs 3111 and 3121 end, and two newprograms 3112 and 3122 start. TV program 3112 is highly popular andtherefore generates a large bandwidth demand 3112′. Program 3122 is notpopular, and therefore generates a limited bandwidth demand 3122′. Someof the additional bandwidth needed by program 3112 is taken from serversthat stop serving assembling devices previously retrieving program 3121,such that the aggregated bandwidth of all three streams(3131′+3122′+3112′) is still below the maximum possible bandwidth 3150,despite the fact that program 3112 is generating a large bandwidthdemand. This example illustrates how the fractional-storage serverssupport almost any demand mixture, as long as the aggregated demand ofall streams is kept below the aggregated maximum capacity of the servers3150. Consequently, the distribution of all of the streams to thefractional-storage servers is approximately unrelated to the changes inbandwidth demand for programs carried by each stream; each stream can beregarded as a sequence that is segmented, erasure-encoded, anddistributed to the participating servers. There is no need to accountfor demand variations during the distribution of each stream, nor isthere a need to know in advance the bandwidth demand for each stream orfor each program within each stream. It is noted that the demandvariations are illustrated as instant variations, but may also begradual and may occur during a program and not necessarily when oneprogram ends and the other begins.

FIG. 17 illustrates one embodiment of fractional-storage servers 697 ato 697(N), wherein each server, or a group of servers, may be ownedand/or connected to the Internet in any combination and by differententities. The following 3 examples illustrate how the assembling devicesbalance the load on the fractional-storage servers. In one exampleservers 697 a and 697 b, server 697 c, and servers 697(N−1) and 697(N)are connected to the Internet 300 via first, second, and third hostingproviders (689 a, 689 b, and 689 c) correspondingly. Assembling device661 can select the servers regardless of the hosting provider, and in amanner that combines erasure-coded fragments from several hostingproviders. At any point in time, the operator of the distributed storagesystem can perform a cost effectiveness analysis of the hosting and datatransport services provided by each hosting provider, and look for newhosting providers as candidates for replacement of one or more of thecurrent hosting providers. If such a replacement is found, such as whena better hosting deal can be obtained, the distributed storage operatorcan terminate the services of such hosting provider(s), and replace itwith a better deal.

FIG. 18 illustrates one embodiment in which different data centers 1461to 1464 host fractional-storage servers. The servers store erasure-codedfragments encoded with a redundancy factor R greater than one. Aplurality of assembling devices 1499 obtain fragments needed forstreaming contents. No group of servers within any one of the datacenters store more than (1-1/R) of the fragments associated with asingle segment to be reconstructed; meaning that if any one of the datacenters stop delivering fragments, the other data centers still compriseenough erasure-coded fragments needed to decode the fragments. Upontermination of a fragment delivery service from any one of the datacenters, the servers of the data center whose fragment delivery servicewas terminated are deselected for fragment delivery, and other serversin other data centers are selected for fragment delivery instead, whilethe streaming of the contents to affected assembling devices continuesduring this short deselection-reselection process, and withoutdisrupting any ongoing streaming operation. Usually, each data centerhosts more than one server, but a data center may also host a singleserver. In one embodiment, more than 200 servers are hosted in more than20 data centers. In one embodiment, more than 10,000 servers are hostedin more than 100 data centers, and deliver fragments at an aggregatedthroughput of more than 10 Tera-bit per second.

In one embodiment, the assembling devices 1499 use a fragment pullprotocol to retrieve fragments from the servers and to approach newservers, optionally on-the-fly while streaming contents, instead ofservers whose data center's fragment-delivery service was terminated.

In one embodiment, the assembling devices 1499 use a push protocol toobtain fragments from the servers by utilizing multiplesub-transmissions. Servers whose data center's fragment-delivery servicewas terminated are replaced, optionally on-the-fly while streamingcontents, by other servers which operate as the sub-transmissionsources.

In one example, the deselection-reselection process takes a few secondsor less. In one example, the deselection-reselection process is donefaster than it takes to play the content stored in one relatively shortsegment. In one example, the deselection-reselection process is done byassembling devices. In one embodiment, the reselection of servers isdone by a control server.

FIG. 19 illustrates one embodiment in which fractional-storage serverswithin data centers 3661 to 3664 store erasure-coded fragments encodedwith a redundancy factor greater than one. A plurality of assemblingdevices 3699 obtain decodable sets of fragments from subsets of theservers and measure fragment delivery parameters that are indicative ofdelivery performances, such as latency in responding to requests, orfragment loss ratios. Each assembling device can readily make themeasurements on fragments sent to it. Decisions are constantly made bythe assembling devices, a control server, or any other decisioncomponent, regarding selection and reselection of servers participatingin the subsets. The decisions are based on the measured parameters, andare made in order to improve the measured parameters. After many suchdecisions are made for or by many assembling devices, it is possible toestimate the performances of the different data centers. A data centerthat is underperforming relative to other data centers is likely tofeature one or more of the following: (i) delivers fewer fragments toassembling devices as compared to other data centers, (ii) incurs highercost per fragment delivery, and thus is less cost effective compared toother data centers, (iii) utilizes a lower percentage of the fragmentdelivery bandwidth available to it, as compared to other centers, and/or(iv) exhibits any other measurable degradation in performance level,that is a result of server participation in subsets, and that can beused to differentiate it over well performing data centers. Thepreference of the assembling devices, or other decision component, forsome servers over other servers creates a “natural selection” processthat can be utilized to distinguish well performing data centers overunderperforming data centers. After the data centers are distinguished,decisions can be made regarding a future utilization of each center.

FIG. 19 and FIG. 20 illustrate some of the above principles andembodiments, in accordance with one example. Data centers 3661 to 3664include fractional-storage servers. Multiple assembling devices 3699obtain erasure-coded fragments from the servers. At first, the fragmentdelivery throughputs 3651 to 3654 delivered by data centers 3661 to 3664over communications lines 3671 to 3674 respectively, are approximatelyequal to each other. Over time, the assembling devices measurefragment-delivery parameters associated with servers of the differentcenters, and select subsets of servers from which to obtain decodablesets of fragments accordingly. The measured parameters associated withcenter's 3661 servers are not as good as the parameters measured fromother servers. Center's 3661 servers are therefore less frequentlyselected by assembling devices 3699, and the result is a reduction infragment delivery throughput from that center from 3651 to 3651′. At thesame time, the measured parameters associated with center's 3664 serversare better than parameters measured by assembling devices from otherservers. Center's 3664 servers are therefore more frequently selected byassembling devices, and the result is an increase in fragment deliverythroughput from that center from 3654 to 3654′. The performance of thedifferent data centers can now be compared, and decisions can be maderegarding the future utilization of the center's resources. Thefollowing two examples illustrate performance comparisons andcorresponding decisions.

In one embodiment, a distributed system is located in a few to dozens ofdata centers (also known as server farm or datacenter), located close toor on the Internet backbone, together housing at least 100fractional-storage CDN servers. The servers store erasure-codedfragments associated with approximately sequential segments of streamingcontents, with a storage gain of at least 5, and transmit the storedfragments on demand to assembling devices approximately according to thesequential order of the segments. In many cases, the data centersprovide a convenient place to place the CDN servers close to or on theInternet backbone. A data center can be also a collocation center, or anInternet Exchange Point. In one example, a single data center can housemany fractional-storage CDN servers.

In one example, a streaming system comprising at least several hundredsof fractional-storage CDN servers located close to or on the Internetbackbone, storing erasure-coded fragments encoded with a redundancyfactor greater than one, and associated with approximately sequentialsegments of streaming contents. At least 100,000 assembling devicesconcurrently obtain fragments from the CDN servers, wherein the systemachieves efficient load balancing and fault tolerance between thevarious CDN servers by determining for each of the assembling devicesfrom which servers to obtain the fragments.

In one example, a system comprising at least 1,000 fractional-storageCDN servers is connected to the public Internet. The servers storeerasure-coded fragments associated with approximately sequentialsegments of streaming contents, with a storage gain greater than 5, andtransmit the stored fragments on demand to assembling devicesapproximately according to the sequential order of the segments. Whereinthe aggregated bandwidth utilized by the servers for transmitting thefragments to the assembling devices exceeds 1 Giga bit per second timesthe number of the CDN servers. In one optional example, the systemcomprises at least 10,000 fractional-storage CDN servers and theaggregated bandwidth utilized by the servers exceeds 10 Giga bit persecond times the number of the CDN servers.

In some embodiments, expressions like “approximately sequentialsegments” may denote one or more of the following non-limiting options:segments that are sequential (in time or according to a file's order),segments that are approximately sequential (such as segments with someinterlace, or segments without a great amount of non-sequential data),segments generated sequentially and/or approximately sequentially fromdifferent components of content (such as storing the i-frames andp-frames of a compressed content in different segments), and/or othersequential or approximately sequential segmentation after classificationor separation into different components and/or elements.

In one embodiment, the assembling device categorizes the servers intotwo categories: (i) fastest responding servers, and (ii) slowerresponding servers, and approximately avoids initial fragment requestsfrom the fastest responding servers, such that if additional fragmentsare needed, they are quickly retrieved from the fastest respondingservers. Avoiding retrieval from the fastest responding servers wheninitially requesting the fragments of a segment increases the chances ofretrieving a substitute fragment, needed to compensate for the lostfragments, from the fastest responding servers, and enables fastcompensation that is needed for fast presentation of the streamingcontent. Categorizing the servers may be performed by registeringmeasured latencies of servers responding to fragment requests by theassembling device.

In one embodiment, a plurality of fractional-storage servers, which maybe located almost anywhere around the globe, configured to storeerasure-coded fragments associated with segments of streaming content.An assembling device, which may be located almost anywhere around theglobe, configured to request, using a fragment pull protocol over theInternet, a set of fragments. The assembling device is furtherconfigured to compensate for lost fragments by requesting additionalerasure-coded fragments that are needed to reconstruct the segments.wherein the bandwidth of the streaming content is bounded approximatelyonly by the incoming bandwidth of the assembling device.

In one embodiment, fractional-storage CDN servers configured to storeerasure-coded fragments associated with approximately sequentialsegments of streaming content. An assembling device located at a pointfeaturing an average one-way network-related latency of more than 50milliseconds between the assembling device and the servers obtains afirst set of fragments, approximately according to the sequential orderof the segments, and compensates for lost fragments by obtaining asecond set of erasure-coded fragments that are needed to reconstruct thesegments. Wherein the bandwidth of the streaming content is boundedapproximately only by the incoming bandwidth of the assembling device.Optionally, the assembling device is configured to utilize a fragmentpull protocol to obtain the fragments. Optionally, the assembling deviceutilizes a push protocol to obtain the fragments.

FIG. 21 illustrates one embodiment of a server array including servers399 a to 399(N) storing erasure-coded fragments 390 a to 390(N)associated with content. In order for assembling device 661 toreconstruct a segment 101 a of the content, it has to retrieve at leastK erasure-coded fragments. In one example, k=4 and the assembling device661 chooses approximately randomly from which servers to retrieve the 4different erasure-coded fragments. It chooses to retrieve fragments 390a, 390 c, 390(N−1) and 390(N), which are noted as group 573, andreconstruct the segment 101 a. Consequent segments of the content arereconstructed in a similar fashion, and the content may eventually befully retrieved by combining all relevant segments. If the assemblingdevice 661 cannot reconstruct the segment 101 a, it retrieves one ormore additional unique erasure-coded fragments, and tries again.

Referring back to FIG. 21, in one embodiment, the content beingdistributed supports stream presentation, and segment 101 a is of smallsize, to enable content presentation by assembling device 661 shortlyafter beginning the reception of the segment (or any other segment ofthe content). For example, segment 101 a is 96 KByte, allowing a 5 Mbpsdownload speed receiver to obtain the entire segment (by requestingenough erasure-coded fragments to enable the reconstruction of thesegment, and such that the total size received of all requestederasure-coded fragments is slightly larger than the segment) afterapproximately 0.2 seconds from request, and beginning the presentationshortly or right after the successful decoding and reconstruction ofsegment 101 a.

In some embodiments, the fragments are small enough to be contained inone packet. In one embodiment, each fragment is about 1400 bytes, andcan fit into one UDP or RTP packet transmitted over Ethernet. Thestateless nature of UDP and RTP allows the servers to send one packetwith one fragment very quickly, without the need for any acknowledgementor hand shaking In some embodiments, the fragment pull protocol requestsuse one stateless packet, like UDP or RTP. In one embodiment, theassembling device requests about 100 fragments approximately inparallel, using 100 separate requests or one or few aggregated requests.About 100 servers respond by sending about 100 fragments, eachencapsulated in one stateless packet, after a short delay, and theassembling device receives the fragments within a fraction of a second.Assuming an Internet round trip delay of 100 ms, and server processinglatency of 100 ms, then after 200 ms the assembling device startsreceiving all 100 fragments. With a modem of 5 Mbps, and assuming 1400bytes per fragment, all 100 fragments are received 1400×100×8/5 Mbps=224ms after the initial delay, meaning that content can be presented200+224=424 ms after request (decoding and other process time has beenignored in this example).

The following embodiments describe processes for on-the-flyerasure-coded fragment retrieval from fractional-storage servers.

In one embodiment, a method for obtaining erasure-coded fragments fromfractional-storage servers to reconstruct a segment includes thefollowing steps: (i) identifying the next segment to be obtained;optionally, the segments are approximately sequential segments ofstreaming content obtained according to their sequential order; (ii)optionally, determining the minimum number of fragments needed toreconstruct the segment; (iii) are enough identified relevant servers(i.e. servers storing the required fragments) available from the processof obtaining prior segment/s? (iv) if no, identifying enough relevantservers; (v) if yes, requesting enough fragments from the identifiedrelevant servers; if less than enough fragments are obtained from theidentified relevant servers, go back to step iv and identify additionalrelevant server/s; (vi) reconstruct the segment from the obtainedfragments; and (vii) optionally, go back to step i to obtain the nextsegment.

In one embodiment, a method for obtaining erasure-coded fragments fromfractional-storage servers to reconstruct multiple segments includes thefollowing steps: (i) identifying multiple segments to be obtained,optionally according to their sequential order; (ii) optionally,determining the minimum number of fragments needed to reconstruct thesegment; (iii) optionally, determining the number of fragments to beobtained approximately in parallel; (iv) are enough identified relevantservers available from the process of obtaining prior segment/s? (v) ifno, identifying enough relevant servers; (vi) if yes, requesting enoughfragments from the identified relevant servers, optionally in paralleland according to the sequential order of the segments; (vii) if lessthan enough fragments are obtained from the identified relevant servers,go back to step iv and identify additional relevant server/s; (viii)reconstructing the segment/s from the obtained fragments; and (ix)optionally, go back to step i to obtain the next segments.

In one embodiment, a method for obtaining erasure-coded fragments fromfractional-storage servers to reconstruct a segment in a burst modeincludes the following steps: (i) identifying the next segment to beobtained; (ii) optionally, determining the minimum number of fragmentsneeded to reconstruct the segment; (iii) are more than the minimumnumber of relevant servers available from the process of obtaining priorsegment/s? (iv) if no, identifying more than the minimum relevantservers; (v) if yes, requesting more than the minimum number offragments needed to reconstruct the segment; if less than enoughfragments are obtained, go back to step iv and identify additionalrelevant server/s; (vi) reconstructing the segment from the obtainedfragments; and (vii) optionally, go back to step i to obtain the nextsegment.

The various methods for obtaining erasure-coded fragments from thefractional-storage servers for reconstructing one or more segments maybe combined as needed. In one example, the initial segment/s areobtained using a burst mode and the following segments are retrievedwithout requesting extra fragments. In another example, the initialsegment/s are obtained approximately in parallel and optionally using aburst mode, and the following segments are obtained one by one andoptionally without requesting extra fragments. The fragments may beobtained using a pull protocol and/or a push protocol. Moreover, theservers from which to retrieve the fragments may be selected accordingto one or more of the various discussed methods for selecting theservers and/or load balancing the servers.

FIG. 22 illustrates one embodiment of real time streaming contentretrieval from fractional-storage servers. An assembling device begins aprocess of obtaining streaming content 700 for presentation. Starting atT1, the assembling device requests erasure-coded fragments 720 a to720(K). By T2, all K erasure-coded fragments are obtained, and at timeT2 b until T4, erasure-coded fragments 720 a to 720(K) are decoded intosegment 710 a. The retrieval time of the erasure-coded fragments and thesegment decoding time should be equal to or faster than thecorresponding presentation time, in order to enable a continuouspresentation, once presentation begins at T5. T2 b minus T2 is a shortdelay, and can be fractions of a second. Subsequent erasure-codedfragments 730 a to 730(K) are retrieved between T2 and T3, and aredecoded into subsequent segment 710 b between T4 and T6.

In one example, the streaming content 700 is encoded at 1 Mbps, and thesegment size is 96 Kbytes. The presentation of each segment takes about0.77 seconds. Retrieving fragments 720 a to 720(K) takes no more than0.77 seconds, meaning that the assembling device's connection bandwidthmust be 1 Mbps or higher. Decoding segment 710 a takes no more than 0.77seconds. If a small delay of 0.2 seconds is assumed for both T2 b minusT2 and T5 minus T4, then T5 can start at 0.77+0.2+0.77+0.2=1.94 secondsafter T1, meaning that presentation can begin about 2 seconds followingrequest of the first erasure-coded fragment. In another example, theretrieval process and the decoding process are performed faster than thereal time presentation bounds, therefore enabling a shorter time to playand a download rate that exceeds the presentation rate.

In one embodiment, the erasure-coded fragments 720 a to 720(K) areretrieved in approximately random order, or any other order, as long asat least the K erasure-coded fragments needed for decoding the segment710 a are available until time T2.

In one embodiment, the fragments associated with sequential segments ofstreaming content are delivered to an assembling device as a pluralityof sub-transmissions. In this case, each fractional-storage serverparticipating in the delivery of the fragments to the assembling devicesends a transmission to the assembling device comprising a sequence oferasure-coded fragments. This transmission is referred to as asub-transmission. In one example, each sub-transmission contains atleast one fragment per each sequential segment of the streaming content.In one example, the sub-transmission starts at a segment indicated bythe assembling device, and continues from that point onwards,approximately according to the sequential order of segments, until theassembling device instructs the server to stop, or until reaching thelast segment of the content. Each sub-transmission carries only afraction of the fragments (per segment) needed to reconstruct thesegments of the streaming content, such that the combination of at leasttwo sub-transmissions received by the assembling device from the serversallows the assembling device to obtain enough fragments needed toreconstruct each segment.

In one embodiment, each sub-transmission is delivered to the assemblingdevice via a streaming session, such as an RTP session, wherein the RTPpackets transport the fragment sequence approximately according to theorder of the sequential segments. In one embodiment, eachsub-transmission is delivered to the assembling device via an HTTPconnection, or other closed-loop data transfer mechanisms over TCP/IP.In one embodiment, the assembling device may change one or moretransmitting servers on the fly, by instructing the server(s) to stopsending an already active sub-transmission—as may be needed in a case ofan RTP session, and initiating new sub-transmissions from other serversinstead. Replacement of transmitting servers on the fly may be needed ina case of a server failure, network failure, or high load or latencyconditions.

In some embodiments, a push protocol is used to obtain fragments. A pushprotocol may be implemented using one transmission carrying fragmentsfrom a source server to a destination receiver, or may be implementedusing a plurality of sub-transmissions. When using sub-transmissions,each sub-transmission transports a fraction of the fragments needed forsegment reconstruction. Segments may be reconstructed from fragmentsreceived via sub-transmissions after obtaining decodable sets oferasure-coded fragments; optionally one set per segment. Asub-transmission may be transported using an IP stream such as RTP, anHTTPS session, or any other protocol suitable for transporting asequence of fragments between a source server and a destinationassembling device.

FIG. 21 illustrates one embodiment, in which content is segmented anderasure-coded. Fragments 390 a to 390(N), belonging to a first segment,are distributed to servers 399 a to 399(N) respectively. Other fragmentsbelonging to subsequent segments are similarly distributed to servers399 a to 399(N). The servers may use a push protocol to transport thefragments to an assembling device. A push protocol sub-transmission maycomprise a sequence of fragments associated with multiple segments. Inone example, the fragments are ordered according to the sequential orderof the segments in a streaming content. Server 399 a sends a firstsub-transmission to a destination assembling-device. Optionally, thefirst sub-transmission comprises a sequence of fragments starting withfragment 390 a, associated with the first segment, and continuing withfragments belonging to subsequent segments. Server 399 c sends a secondsub-transmission to the destination assembling-device, optionallystarting with fragment 390 c, associated with the first segment, andcontinuing with fragments belonging to subsequent segments. In a similarfashion, servers 399(N−1) and 399(N) send additional sub-transmissionsto the destination assembling-device, each comprising a unique fragmentsequence.

When using a push transmission, the assembling device does notexplicitly ask for each fragment, but instead instructs each of thedifferent servers to start sending it a fragment sequence using asub-transmission. The destination assembling-device receives thesub-transmissions sent by servers 399 a, 399 c, 399(N−1) and 399(N). Itgathers 573 the first fragment from each sub-transmission to reconstructthe first segment 101 a. In a similar fashion, additional fragmentsbelonging to subsequent segments are obtained from thesub-transmissions, and used to reconstruct the segments. It is notedthat any combination of sub-transmissions may be used, as long as adecodable set of fragments is obtained per each segment. It is alsonoted that FIG. 21 illustrates a non-limiting embodiment and asub-transmission may include two or more unique erasure-coded fragmentsper segment.

In one embodiment, the push sub-transmissions is synchronous (allservers sending the fragments of each segment at approximately the sametime). In another embodiment, the push sub-transmission is asynchronousand the arrival of different fragments associated with a specificsegment at the assembling device side may be spread over a long period.This may occur, as an example, when some push servers are faster thanothers. In one embodiment using asynchronous sub-transmissions, theassembling device aggregates whatever fragments it can beforepresentation time of each segment, and then optionally supplementsfragments using a pull retrieval process. A server that does not sendfragments fast enough, and therefore usually causes supplementalrequests, may be ordered to stop the sub-transmission. Another servermay be requested, optionally by the assembling device, to replace theslow server by initiating a new sub-transmission.

In one embodiment, the push-transmissions carry more erasure-codedfragments than needed for segment reconstruction. In one embodiment, thepush transmissions carry fewer erasure-coded fragments than needed forsegment reconstruction, and the remaining fragments are pulled by theassembling device.

FIG. 23 illustrates one embodiment of a fragment pull protocol.Assembling device 861 (also represented by protocol diagram element 810b) obtains erasure-coded fragments from fractional-storage servers 899 ato 899(N) (also represented by protocol diagram element 898), utilizingthe following steps: (i) deciding 810 a which segment to retrieve; (ii)device 861 sending requests to some of the fractional-storage serversfor erasure-coded fragments associated with the desired segment. Forexample, requests 880 a to 880(K) for erasure-coded fragments 890 a to890(K), from servers 899(a) to 899(K), correspondingly; and (iii) theservers respond by sending the requested erasure-coded fragments. Forexample, servers 899 a to 899(K) send 881 a to 881(K) erasure-codedfragments 890 a to 890(K) to device 861. The fragment request andreceipt process begins at T1 c and ends at T1 d. At time T1 d, device861 has enough erasure-coded fragments (K) to reconstruct the segmentselected at 810 a. In one embodiment, the process from T1 c to T1 doccurs in real time, in support of streaming content presentation.

FIG. 24 illustrates a similar process to FIG. 23, where request 890 bfails to result in a reception of erasure-coded fragment 890 b for anyreason (such as a server fault, network congestion, or abnormal latencyconditions). Assembling device 861 therefore issues another request882(K+1) for erasure-coded fragment 890(K+1) in response, and receives883(K+1) the additional erasure-coded fragment 890(K+1) needed toreconstruct the segment.

FIG. 25 illustrates a similar process to FIG. 23, where one or moreextra erasure-coded fragments (in addition to the needed K) arerequested in advance (illustrated as request 880(K+1) for erasure-codedfragment 890(K+1)), such that if, as an example, request 890 b fails toresult in a reception of erasure-coded fragment 890 b, assembling device861 does not have to request new erasure-coded fragments to reconstructthe segment, since there are still at least K erasure-coded fragmentsthat were successfully received and therefore the segment can bereconstructed.

FIG. 26 illustrates a similar process to FIG. 23, where requests forerasure-coded fragments are loaded into one aggregated request 870, thatis sent to one of the fractional-storage servers (the receiving serveris illustrated as protocol diagram element 888 a, and will be alsoreferred to as a “relay server”). In one example, if the relay server is899(N), then, it will forward the request to additional servers 899 a to899 c (protocol element 888 b) via new requests 870 a to 870 c (onbehalf of assembling device 861). Servers 899 a to 899 c will thenrespond by sending the erasure-coded fragments 890 a to 890 c (871 a to871 c) to the assembling device 861. Server 899(N) will send 871(N)fragment 890(N) to the assembling device.

In one embodiment, an assembling device may aggregate several fragmentrequests into one message. The aggregated message is then sent to afractional-storage server, possibly in a payload of a single packet, andoptionally in order to conserve outgoing bandwidth and/or to reduce thenumber of packets needed to convey the requests. The fractional-storageserver may then read the aggregated message and act accordingly bysending a plurality of fragment responses to the assembling device. Thefragment responses may include one fragment at each payload, as is thecase of responding to a single fragment request, or it may include anaggregated response including multiple fragments at each payload.

In one embodiment, an assembling device may control the erasure-codedfragment reception throughput by controlling the rate of fragmentrequest. For example, each of n fragments has a known size S1 to Sn.Therefore, issuing n requests over a period of T will result in anaverage fragment reception throughput of (S1+S2 . . . +Sn)/T. In oneexample, if each fragment is 1500 Bytes, and 64 fragment requests areissued over a period of 0.5 seconds, then the average expected fragmentarrival throughput is (64×1500×8)/0.5=1.53 Mbps. The fragment requestsdo not need to be uniformly spread over the period of 0.5 seconds,although such a spread may result in a more stable throughput, whichmeans that less communication buffering will be needed. Using theabove-described rate-control technique may result in one or more of thefollowing: retrieving the content at a target fragment receptionthroughput; preventing communication buffer spill at the last milenetwork resulting from uncontrolled fragment requests; and/or reducingfragment loss due to averaging the fragment traffic.

The term “fragment pull protocol for high latency” as used hereindenotes a protocol enabling an assembling device to request one or morefragments from one or more providing sources, wherein the time totransmit the one or more fragments in response to the assembling devicerequest, through the slowest communication link connecting theresponding source and the assembling device, is smaller than the roundtrip communication delay between the assembling device and theresponding source, excluding the processing time of the providingsource. For example, if the round trip communication delay betweenIsrael and the USA is about 200 ms, the assembling device requests onefragment sized about 1500 bytes, and the slowest communication link isan ADSL line connecting the assembling device at 1.5 Mbps, then the timeit takes to transmit the requested fragment through the slowestcommunication link is about 1500*8/1500000=8 ms, which is much smallerthan the round trip delay. Many of the disclosed embodiments usingfragment pull protocol may use fragment pull protocol for high latencyfor retrieving the fragments.

In one embodiment, an assembling device transmits aggregated messages toa relay server, including the number of fragments needed per certainsegment, but without identifying the storage servers from whichfragments are to be requested. The relay server selects the appropriatestorage servers to which the fragment requests are to be transmitted,and transmits discrete or aggregated fragment requests, corresponding tothe number of fragments requested by the assembling device, to theselected storage servers. The storage servers receive the fragmentrequests from the relay server, and transmit the requested fragment tothe assembling device. The relay server may select the storage serversaccording to one or more criteria, as long as the selected storageservers store relevant fragments. Optionally, the relay server forwardsthe address of the assembling device to the selected storage servers,and/or adds the address of the assembling device to the fragmentrequests transmitted to the selected servers, in order to enable thestorage servers to transmit the fragment response to the assemblingdevice.

In one embodiment, shifting the process of selecting the storage serversfrom the assembling device to the relay server enables the design of arelatively thin and simple assembling device, having a relatively simplesoftware, since all the assembling device has to decide in order toissue an aggregated fragment request to the relay server is how manyfragments it needs per segment and, optionally, when it needs them.

In one embodiment, an assembling device transmits aggregated messages toa relay server, comprising general information regarding a portion ofstreaming content for which fragments are needed. Optionally, theportion of the streaming content comprises several consecutive segments.In one embodiment, the portion is defined by a starting point and anending point within the streaming content, and the relay server usesthese points to determine the actual segments comprising the portion.Then the relay generates and transmits the corresponding fragmentrequests to the relevant storage servers.

FIG. 27 illustrates one example of geographically distributedfractional-storage servers 399 a to 399 n, in which servers 399 a to 399c are located in Europe 676, servers 399 d to 399 g are located on theeast coast of the US 677, servers 399 h to 399 i are located on the westcoast of the US 678 and servers 399 k to 399 n are located in Japan 679.Assembling devices all over the world obtain erasure-coded fragmentsfrom the globally distributed fractional-storage servers. Thecharacteristics of the fractional-storage system, according to someembodiments, allow the globally distributed assembling devices toexploit the outgoing bandwidth of the globally distributedfractional-storage servers approximately up to the point where allservers 399 a to 399 n utilize their available outgoing bandwidth forcontent delivery.

In one embodiment, the main demand for fragments shifts between thedifferent global locations as the day elapses. For example, at 8 pmPacific Standard Time, the main fragment demand is generated from the USwest coast. At that time, the local time in the east coast is lateevening, the time in Europe and Japan is early morning and noonrespectively, and thus very little fragment demand is generated fromthese regions. The high fragment demand load generated from the westcoast is spread across all of the fractional-storage servers. As the dayelapses, the load generated from the west coast declines, and the mainload shifts to Japan as time there becomes afternoon. When that happens,the servers are still able to supply all content demands, as they arestill able to deliver maximal bandwidth to assembling devices in Japan.As the cycle continues, the main load shifts again from Japan to Europe,from Europe to the US east coast, and from there back to the US westcoast, following a 24-hour cycle. In some embodiments, the servers areable to deliver maximal fragment traffic, resulting from peak demandsoccurring during a day cycle, to anywhere on the globe.

In one example, there are 14 globally distributed fractional-storageservers; each server has a bandwidth of B, and the total capacity of thearray is 14×B. Assuming the total global peak demand during the dailycycle does not exceed Bg, then the system is balanced and can meet alldemands during the daily cycle if Bg<14×B, meaning that B>Bg/14. In thisexample, all servers may be at, or may approach, their peak bandwidthcapabilities for a relatively long period, and feature relatively shortidle periods. In one example, the number of servers in the global arrayis 10,000, from which 2,500 are located on the US west coast, 2,500 onthe east coast, 2,500 in Europe and 2,500 in Japan. In one example, thenumber of servers in the global array is 1,000, from which 100 arelocated on the west coast, 700 on the east coast, 100 in Europe and 100in Japan.

In one embodiment, multiple contents originating from multiple globallocations (and therefore expected to require high loads at differenttimes of day), are all stored on the globally distributedfractional-storage servers. Therefore, the system's bandwidth capacityequals the aggregated bandwidth of its server members, optionallyregardless of which content generates high load, regardless of when theload is generated during the day, and regardless of where the load isgenerated from.

In one embodiment, at some point in time, some portions of the Internetmay become congested at some global locations. The global system assuresthat servers not affected by the congestion handle the excess load, suchthat operation close to peak bandwidth performance is still possible.

In one embodiment, the globally distributed assembling devices retrievefragments from the fractional-storage servers using a fragment pullprotocol, and determining which servers deliver fragments to whichassembling devices load balances the distributed system. In oneembodiment, the globally distributed assembling devices obtain fragmentsfrom fractional-storage servers using a push protocol with multiplesub-transmissions, and determining which servers deliver fragments viathe sub-transmissions to which assembling devices load balances thedistributed system.

FIG. 28 illustrates one embodiment in which assembling devicesdistributed over different time zones together induce fragment traffichaving a reduced peak-to-average traffic ratio, as compared to thefragment traffic induced by assembling devices located in any singletime zone. Graph 1602 illustrates the fragment traffic induced byassembling devices located at a first time zone. The peak of graph 1602occurs during the late afternoon, local time of the first time zone.Similarly, graphs 1603 and 1604 illustrate induced traffic from secondand third time zones. Since the first, second and third time zones aredifferent, the peak traffic of each graph occurs at a different time.The peak-to-average fragment traffic ratios of graphs 1602 to 1604 arerelatively high, since most of the traffic is generated close to thepeak demand. In the case of video traffic, a daily peak-to-averagetraffic ratio of about six is expected during one day, starting at T1and ending at T2. The combined traffic induced by all assembling devicesis the sum of graphs 1602 to 1604, which is schematically illustrated asgraph 1601. Since the peaks of graphs 1602 to 1604 occur at differenttimes, the combined traffic 1601 behaves much more smoothly and haspeaks close to the peaks of graphs 1602 to 1604, resulting in a muchlower peak-to-average traffic ratio, which in some embodiments is abouttwo or three. This means that the fractional-storage servers can beutilized during longer periods of the day when servicing assemblingdevices located at different time zones. In one embodiment, thedistribution of the assembling devices to the different time zonesresults in an approximately flat traffic during the day, having apeak-to-average traffic ratio approaching one. Such a distribution ischallenging in real life deployments, but can be approached byengineering the distribution of the assembling devices over the globe.

Still referring to FIG. 28, in one embodiment, the severs are connectedto the Internet using guaranteed fixed bandwidth communication links,and can together deliver to the Internet fragment traffic of 1610 allday. In this case, it is clear that traffic graph 1601 utilizes thefixed bandwidth capacity 1610 better than any of the graphs 1602 to1604, since it approaches the maximal capacity for longer periods overthe day.

In one embodiment, the servers are spread over two or more continents,and some of the fragments associated with the same segments are storedon different servers located on different continents. This achievescontent placement diversity, and results in better immunity to differentnetwork and server faults.

FIG. 29 illustrates one embodiment in which US-based fractional-storageservers 399 a′ to 399 n′ deliver erasure-coded fragments to assemblingdevices spread over the globe. The assembling devices spread over theglobe induce a total fragment traffic from the US-based servers having areduced peak-to-average traffic ratio, as compared to the fragmenttraffic induced by assembling devices located in any single time zone.In one example, 5,000 fractional-storage servers are located in the USand service 10 million assembling device subscribers spread over theglobe. At a first period during the day, the servers delivererasure-coded fragments concurrently to 2 million assembling deviceslocated primarily in Japan. At a second period during the day, theservers deliver erasure-coded fragments concurrently to 2 millionassembling devices located primarily in Europe. At a third period duringthe day, the servers deliver erasure-coded fragments concurrently to 2.5million assembling devices located primarily on the East Coast, and ½million assembling devices located primarily on the West Coast. At afourth period during the day, the servers deliver erasure-codedfragments concurrently to ½ million assembling devices located primarilyon the East Coast, and 2.5 million assembling devices located primarilyon the West Coast. According to this example, the servers are capable ofdelivering a peak fragment traffic resulting from the demand of at least3 million assembling devices concurrently.

In one embodiment, the servers are spread over different time zones.Different servers located at different time zones usually encounter peakload conditions at different times, especially if they share resources,such as communication link to the Internet, processing resources,storage, Tier-1 ISP networks, backbone networks, or any other resourceswith local servers delivering general Internet traffic. Load conditionsmay refer to actual load on the servers, load on a communications linkconnecting the server to the Internet, load on a local backbone orTier-1 network, or any type of condition in which additional fragmenttraffic will contribute to service degradation. In the case of a loadcondition, it is advantageous to refrain from obtaining fragments fromservers that directly contribute to the load, and to try to obtainfragments from servers that do not directly contribute to the load.Servers encountering load conditions below a certain threshold areusually found somewhere, as they are spread over different time zones,and these servers are the preferred fragment sources.

FIG. 30 illustrates one example of different loads at different timesfor different time zones. Graphs 641 a, 641 b, 641 c and 641 d representload levels encountered by server groups 679, 676, 677 and 678respectively, located in the Far East, Europe, the US east coast, andthe US west coast respectively. In one example, the loads refer totraffic levels on communication links connecting the data centers, inwhich the servers are placed, to the Internet. In this case, the trafficmay be general Internet traffic generated by servers and otherapplication/s not necessarily related to fragment delivery, and thecommunication links can also be referred to as shared links, as they areused to transport both fragment traffic and general Internet traffic.During a 24-hour period, all encountered load levels complete one cycle.The load level graphs are shifted in time in respect to each other,according to the time shifts between the various time zones around theworld in which the different server groups are located. As an example,graph 641 a represents load encountered by the servers in the Far East,with a peak load occurring about 7 hours before graph 641 b representingload encountered by the servers in Europe.

At each arbitrary point in time, server groups around the world mayencounter different load conditions. As an example, at point 642 a,server group 679 encounters medium load conditions, server group 676encounters peak load conditions, and server groups 677 and 678 encounterlow load conditions. Therefore, at the point in time 642 a, it isbeneficial for assembling devices to obtain erasure-coded fragments onlyfrom server groups 677, 678, and maybe 679. Server group 676 encounterspeak load conditions, and therefore will not be approached by theassembling devices. At a different point in time 642 b, the worldwideload conditions change, such that server groups 679 and 676 encounterlow load conditions, and server groups 677 and 678 encounter high loadconditions. At this point, assembling devices will obtain fragments fromservers groups 679 and 676 and will refrain from approaching servergroups 677 and 678.

In one embodiment, the load conditions encountered by each server group,or by specific servers, are published by the servers. In one embodiment,the load condition level encountered by each server is sent to eachassembling device as a response to an erasure-coded fragment request.

In one embodiment, the communication link transporting fragments from aserver or group of servers to the Internet is owned by a data centeroperator. The data center operator publishes the load conditionassociated with the link. The published information is used to selectservers that transmit fragments via relatively unloaded links ascompared to other links.

In one embodiment, the load conditions encountered by a server aredetected by an outside source, such as an assembling device or a controlserver, using one of the following methods: (i) detecting an increasedlatency in responding to a request such as a fragment pull protocolrequest, (ii) detecting a certain level of latency variance, (iii)detecting a certain level of packet or fragment loss, and/or (iv)detecting outages in server's traffic.

FIG. 31 illustrates one embodiment of data centers communicating viashared links. Fractional-storage servers 1699 a to 1699 c are collocatedwith at least one general server 1698 in a data center 1671. All theservers are connected to the Internet via a shared communication link1681. Therefore, erasure-coded fragment traffic transmitted by thefractional-storage servers and general Internet traffic transmitted bythe general server are mixed together on the shared link 1681.Similarly, fractional-storage servers 1699 d to 1699 g are collocatedwith at least one general server 1699 in a data center 1672, and sharethe same communication link 1682 to the Internet. In one embodiment, thefractional-storage servers are selected for fragment transmittal whenthe communication link through which they transmit fragments to theInternet is loaded below a certain level. This principle is demonstratedby the following example: assuming that any three fractional-storageservers out of 1699 a to 1699 g store a decodable set of fragments, thethree servers will be selected according to the load of the link throughwhich they communicate. If the general server 1698 transmits a highlevel Internet traffic via link 1681, and this traffic is close to themaximum capacity of the link, then using any of servers 1699 a to 1699 cis not advisable. Instead, in a case where the general server 1699 doesnot create a high level traffic and link 1682 is relatively free totransport fragments, any three servers out of servers 1699 d to 1699 gmay be used. When the fractional-storage servers deliver fragments tomany assembling devices, servers transmitting via relatively unloadedlinks are preferred, such that the end effect is that servers 1699 d to1699 g deliver a higher fragment load than servers 1699 a to 1699 c. Inother words, servers 1699 d to 1699 g participate in more sub-sets ofservers delivering decodable sets of fragments to assembling devicesthan servers 1699 a to 1699 c.

FIG. 32 illustrates one embodiment of alternative servers communicatingvia shared networks. Fractional-storage servers 1699 a′ to 1699 c′transmit erasure-coded fragment traffic over Internet backbone networksor Tier-1 networks 1661 and 1662. The fragment traffic and the generalInternet traffic transported via the networks are mixed together on thenetworks. Similarly, fractional-storage servers 1699 d′ to 1699 g′ areconnected to Internet backbone networks or Tier-1 networks 1663 and1664. In one embodiment, the fractional-storage servers are selected forfragment transmittal when the networks through which they transmitfragments to the Internet are loaded below a certain level. Thisprinciple is demonstrated by the following example: assuming that anythree fractional-storage servers out of 1699 a′ to 1699 g′ store adecodable set of fragments, the three servers will be selected accordingto the load of the network through which they communicate. If thegeneral Internet traffic transported via networks 1661, 1662 is close tothe maximal capacity of the networks, then using any of servers 1699 a′to 1699 c′ is not advisable. Instead, in a case where networks 1663,1664 are relatively unloaded with general Internet traffic, any threeservers out of servers 1699 d′ to 1699 g′ may be used. When thefractional-storage servers deliver fragments to many assembling devices,servers transmitting via relatively unloaded networks are preferred,such that the end effect is that servers 1699 d′ to 1699 g′ deliver ahigher fragment throughput than servers 1699 a′ to 1699 c′. In otherwords, servers 1699 d′ to 1699 g′ participate in more sub-sets ofservers delivering decodable sets of fragments to assembling devicesthan servers 1699 a′ to 1699 c′.

In one embodiment, the traffic loads on the shared links 1681 and 1682,or shared networks 1661, 1662 and 1663, 1664 change to below a firstlevel and above a second level, and the servers are dynamically selectedaccordingly. In one embodiment, the changes in the traffic loads resultfrom changes in local Internet traffic demands during a 24-hour cycle.Different servers are located in different time zones, such that thepeak of the changing traffic load occurs at different times fordifferent servers. Servers transmitting via relatively unloaded links ornetworks are preferred over servers transmitting via relatively loadedlinks or networks as the load cycle progresses. In one embodiment, theload changes below a first level and above a second level for differentlinks or networks at different times, and the servers are selectedaccordingly. For example, only servers that communicate via links ornetworks loaded below the first level are approached by the assemblingdevices.

In one embodiment, when the shared link or network is loaded below afirst level, the number of sub-sets in which the servers accessed viathe shared link or network are allowed to participate is increased inorder to increase the fragment consumption from these servers. When theshared link is loaded beyond a second level, the number of sub-sets isdecreased. In one example, the amount of fragment traffic transmitted bya server is directly coupled to the number of sub-sets in which theserver participates.

In one embodiment, the maximum number of sub-sets of servers deliveringdecodable fragments to assembling devices in which the servers accessedvia the shared links 1681 and 1682 or shared networks 1661,1662 and1663, 1664 are allowed to participate is approximately a decreasingfunction of the throughput of the general Internet traffic via theshared link or network. In one example, as the general trafficincreases, the server participates in fewer sub-sets, and above acertain point the server does not participate in any of the sub-sets.

In one embodiment, an assembling device will refrain from requestingfragments from a server encountering load conditions close to maximalload, or above a certain threshold. This mechanism may be used to lowerthe cost of placing a server or a virtual server in a colocation centeror any other data center, as the geographically distributedfractional-storage servers do not consume bandwidth and/or processingresources during peak load periods. Furthermore, this mechanism may beused to lower the cost of Internet bandwidth connections to thegeographically distributed fractional-storage servers, as the servers donot consume Internet bandwidth during peak load periods.

In one embodiment, the selection of which fractional-storage serversdeliver erasure-coded fragments to which assembling devicesapproximately determines the network paths through which the fragmentsare transported. When the system has a redundancy factor greater than 1,there is a degree of freedom in selecting the servers that can deliver adecodable set of fragments to an assembling device. If the servers arespread over different networks, then each server, or groups of servers,may have different networks path through which fragments flow whentransmitted to an assembling device. Selecting the servers thereforemeans selecting network paths through which fragments are delivered toan assembling device. As the redundancy factor, the storage gain, andthe diversity at which servers are spread over different networksincrease, so does the number of potential network paths resulting fromserver selections. The selection of paths, via selection of servers, canbe used to avoid congested networks, to prefer certain paths that aremore cost effective, or to optimize any other criterion related tofragment flow paths.

FIG. 33 to FIG. 35 illustrate the influence of selecting source serverson backbone traffic. FIG. 33 illustrates one example whereinfractional-storage servers 3599 a to 3599 j are grouped in threelocations 3541, 3542, and 3543, connected to the Internet via networks3505, 3402, and 3509 respectively. Assembling devices 3537, 3538, and3539 are connected to the Internet and obtain fragments from theservers. Assuming any three servers can be used to deliver decodablesets of fragments to the assembling devices, servers 3599 a, 3599 d, and3599 h are selected to deliver fragments to assembling device 3539. Inthis case, the resulting three network paths through which fragmentsflow to the assembling device are (i) from server 3599 a: first path3509, 3501, 3403 (ii) from server 3599 d: second path 3505, 3503, 3501,3403, and (iii) from server 3599 h: third path 3402, 3508, 3502, 3501,3403.

FIG. 34 illustrates one example wherein networks 3502, 3504, and 3508get congested with Internet traffic, not necessarily as a result offragment traffic generated by servers 3599 a to 3599 j, and possibly asa result of general Internet traffic. The third path includes two of thecongested networks: 3508 and 3502, and should therefore be avoided. Thismeans that another server, instead of 3599 h, has to be selected, suchthat it does not result in a fragment delivery path comprising networks3508 and 3502. Server 3599 b is therefore selected, resulting in afragment delivery path of 3509, 3501, 3403, which is similar to thefirst path already delivering fragments from server 3599 a. Assemblingdevice 3538 will use the servers 3599 h to 3599 j, as they are the onlyservers that avoid the congested networks. The path in this casecomprises networks 3402 and 3401. Assembling device 3537 can use anythree of the servers belonging to groups 3541 and 3543.

In one embodiment, the different networks are associated with differentcosts. The cost may be related to any of the following parameters, orother parameters relevant to transporting fragments over a network: (i)network's congestion level, (ii) network's remaining capacity, (iii)network's packet loss, (iv) network's latency, (v) network's latencyvariance, and/or (vi) the fee for transporting bits over the network. Inone example, selecting which servers deliver fragments to whichassembling devices is performed such that the resulting fragmentdelivery paths comprise networks having the least aggregated cost, or acompetitive aggregated cost compared to alternative paths. FIG. 35illustrates one example of assigning costs to network paths. Each of thenetworks is associated with a cost of 1 to 4. The higher the cost, themore congested the network. Assembling device 3539 can obtain fragmentsfrom either server group 3541, 3542, or 3543. The resulting three pathshave the following aggregated costs: (i) first path, from group 3543:4+1+1=6, (ii) second path, from group 3541: 3+1+1+1=6, (iii) and thirdpath, from group 3542: 1+2+2+1+1=7. The servers are selected from thefirst and second groups, as the resulting path cost is 6. Servers fromthe third group are usually not selected, as the resulting path cost is7.

FIG. 36 illustrates one embodiment wherein the selection of whichservers deliver fragments to which assembling devices is used todetermine network paths for fragment delivery. The servers are selectedsuch that the resulting paths: (i) avoid certain loaded routers, and/or(ii) comprise routers having an aggregated cost lower than otherpossible paths. Fragment traffic going from groups of servers 3541,3542, 3543 to an assembling device 3539 may pass through any of therouters 3501 to 3506, depending on which three servers are selected forfragment transmission. In one example, router 3506 is congested.Therefore, only serves 3599 d to 3599 g and 3599 h to 3599 j areconsidered for fragment delivery, in order to avoid transporting thefragments via the congested router 3506.

Network paths, networks, and/or servers, which should be avoided, may beidentified using one or more of the following embodiments. In oneembodiment, the operator/owner of the networks/routers indicates thatcertain networks/routers are to be avoided. In one embodiment, thenetworks/routers are associated with a cost that is used for selectingthe paths. In one embodiment, the different paths are empiricallychecked by transporting traffic from servers to assembling devices, andmeasuring parameters such as latency, latency variance, fragment orpacket loss, and/or traffic outages. In one embodiment, certainnetworks/routers are to be avoided during a certain period of the day,and can be used during another period of the day. For example, anInternet bandwidth provider has a high traffic load on one of itsnetwork links during the afternoon, but this same link is almost free oftraffic during the early morning. In this case, the provider canindicate that fragments can be delivered via the link only during earlymornings. In another example, an Internet backbone provider has a hightraffic load on one of its Tier-1 networks during the evenings, and amoderate load during the noon period. In this case, the process ofselecting the fragment delivering servers will consider this, and selectdelivery paths comprising the Tier-1 network only during the noonperiod.

In one embodiment, after obtaining some data regarding some of theloads, availabilities, losses, costs, preferences, and/or any other datathat may influence the selection of the servers, algorithms and/ortheorems such as Minimax (also known as Minmax) may be used foroptimizing the selections.

In some embodiments, the path though which a fragment will flow from aserver to an assembling device may be estimated using one or more of thefollowing: (i) TraceRoute functions to map routers between the variousservers and the assembling device, or (ii) obtaining a topological mapof the Internet, and estimating the paths accordingly. The estimatedpath may then be used to shape the actual fragment flow paths byselecting fragment-delivering servers. In one embodiment, the paththrough which fragment flow is unknown, and the determination of whichservers deliver fragments to which assembling devices is performedapproximately randomly, until an indication is received that a certainnetwork, or router, or groups of such, are avoided.

Referring again to FIG. 8 with device 661 o as a non-assembling CPE,such as a STB, PC or gaming console, capable of performing standardrequest, reception, and decoding of video over IP network. In oneembodiment, server 661 s—also referred to as proxy server, assemblingserver, and in some cases assembling device—performs three primaryfunctions: (i) receipt of content requests from non-assembling clientdevice 661 o; (ii) assembly of content, as requested by client 661 o,from the fractional-storage servers and optionally from the bandwidthamplification devices; (iii) optionally, conversion of the assembledcontent into a streaming format; and (iv) transmission of the streamingcontent to the requesting client 661 o. Client 6610 can then store thecontent, or present it. In one embodiment, the assembled content is ageneral web content, including HTML, FLASH or any other data format thatcan be found in a web-based site.

In one embodiment, although server 661 s is illustrated as beingconnected to network 300 on one side and to network 300 n on the other,server 661 s may also be connected to another network element, such as arouter, which makes the topological connection between networks 300 and300 n. In that case, server 661 s communicates with both networks 300and 300 n via the other network element.

In one embodiment, a CDN is created by the aggregated bandwidth andstorage capacity of the participating erasure-coded fractional-storageservers. In one example, a large scale CDN includes several hundreds orthousands of fractional-storage servers connected to the Internet. Theseservers send erasure-coded fragments to a large number, potentiallymillions, of assembling devices. In order to keep costs low for sendinga large number of fragments from fractional-storage servers toassembling devices, the servers are located on the Internet backbone, orclose to it.

The current Internet backbone primarily comprises different Tier one ISP(or other) networks that interconnect at various Internet ExchangePoints (IX or IXP), using peering agreements. Tier one ISPs, or otherbackbone-forming network entities, can reach any portion of the Internetvia other Tier one ISPs or other backbone-forming networks, withoutpaying any Internet transit fee, and solely by utilizing mutual peeringagreements. In order to gain access to large amounts of inexpensivebandwidth, the fractional-storage servers are typically located on theInternet backbone. This means that the servers are either co-located(and connected) with a core switching router that interconnects theInternet backbone networks at an IXP, or, alternatively, co-located (andconnected) with a router which is part of the backbone network,typically located at a data center or co-location center.Fractional-storage servers can also be located close to the Internetbackbone, which means that they are co-located (and connected) with arouter which is part of a Tier two ISP network, which has a highbandwidth connection with at least one Tier one operator, to which itpays transit fees in order to potentially reach all portions of theInternet. FIG. 37 illustrates one example of a fractional-storage server3001, which is one of a plurality of servers forming a large-scale CDN,located on the Internet backbone by being connected to the Internetbackbone via IXP 3091. In a second example, fractional-storage server3002 is located on the Internet backbone by being connected to a Tierone backbone network 3080. In a third example, fractional-storage server3011 is located close to the Internet backbone by being connected to aTier two ISP network 3070, which is connected to the backbone via Tierone ISP network 3081. In one embodiment, a typical fractional-storageserver is located on the backbone or close to the backbone by beingattached to a switching router via a high bandwidth port, such as a 1Gbps, 10 Gbps, or a higher bandwidth port, such as high-speed Ethernetport, usually carried over a fiber, or suitable short-distance copperlines. In one embodiment, in a typical deployment using high bandwidthconnections (in 2009 terms), each of about 1,000 fractional-storageservers is located on the backbone or close to the backbone and isconnected to the backbone via a dedicated (guaranteed bandwidth) 1 GbpsEthernet port, resulting in an aggregated throughput of 1,000 Gbps,which can serve about one million subscribers of standard definitionstreaming video, such as client device 3020, simultaneously. Suchaggregated bandwidths would have required a substantially larger numberof fractional-storage servers, had they been connected to otherlocations in the Internet, such as at edges of the Internet (close tolast mile networks), Tier 3 ISPs, or at the user premises. Moreover, insome embodiments, the cost of streaming the mentioned 1,000 Gbps whenthe fractional-storage servers are located on the Internet backbone, orclose to the Internet backbone, is expected to be significantly lowerthan what is expected when the servers are located elsewhere asmentioned before.

FIG. 38 illustrates one example where an assembling server 4020 islocated at the juncture 4010 between two networks: the first network isan ISP transit network 4014 that connects the juncture to the Internetand provides Internet transit via a switching router 4015, and thesecond is a last mile network 4041 that connects end users 4051 to theInternet via a switch 4031 (located, for example, inside a CentralOffice, a Head-End, or a street-level cabinet). In one embodiment, thejuncture 4010 is a network operated by a local ISP that pays transitfees for Internet traffic passing through the transit network 4014, andlast mile fees for traffic passing through the last mile network 4041. Aunique property of the juncture 4010 is that it is possible for anassembling server 4020 located at the juncture to receive erasure-codedfragments sent by fractional-storage servers, such as 4001 and 4002, toassemble content, and to stream the content to a client 4051 via thelast mile network 4041, without incurring any additional costs incomparison to other scenarios, such as where Internet packets flow fromthe Internet backbone to a Tier two ISP network to the Internet backboneand to the last mile network. In other words, since the assemblingserver 4020 is located at the juncture, it does not create any extratraffic via networks 4014 and 4041. The assembling server can also belocated at or close to an edge of the Internet, which may include thejuncture, or a point above server 4015, such as at the transit network4014 connecting the juncture to the Internet. When located at or closeto an edge of the Internet, the assembling server has the potential notto incur additional transit fees as a result of the relaying operation,since approximately the same traffic would have to pass via the sametransit network in a normal scenario. Another beneficial location forthe assembling server is at the home premises, since, clearly, arelaying operation performed there does not add any significant trafficto higher levels of the network. In contrast to the above-suggestedlocations, in some cases an assembling server may be located at anarbitrary point on the backbone, or at other high-level points of theInternet, where it incurs additional transit fees, as fragmentsassembled by the server flow once over an Internet transit network goingfrom a fractional-storage server to the assembling server, and then asecond time when streamed by the assembling server to a destinationclient over an Internet transit network.

By using a pull protocol or a push protocol with multiplesub-transmissions, the assembling device can obtain erasure-codedfragments from one, two or more different arrays of CDN servers and/orbandwidth amplification devices seamlessly.

In one embodiment, when a CDN server receives a request for anerasure-coded fragment, it may supply the erasure-coded fragment orsupply an address of a bandwidth amplification device having an image ofthe requested erasure-coded fragment. Optionally, a bandwidthamplification device storing one erasure-coded fragment of a specificcontent also stores an image of some or all other erasure-codedfragments associated with the specific content (which are stored on thespecific CDN server). Alternatively, the bandwidth amplification devicestores unique erasure-coded fragments generated from the same segmentsused for generating the erasure-coded fragments stored on the specificCDN server. In these cases, the assembling device may approach thebandwidth amplification devices instead of the CDN server for therelevant erasure-coded fragments of the specific content until (i) theend of the content; (ii) a predefined time period elapses; (iii)receiving an appropriate message; or (iv) a combination of theaforementioned.

In one embodiment, an assembling device tries to obtain an erasure-codedfragment or sub-transmission from the relevant server, and if the serverdoes not have the necessary bandwidth to respond with fragment/s, theserver relays the fragment request/s to relevant bandwidth amplificationdevices. The relevant bandwidth amplification devices can then send thefragment/s directly to the assembling device.

In one embodiment, unique erasure-coded fragments can be distributedbetween two types of devices: (i) high bandwidth fractional-storageservers, such as CDN servers, and (ii) relatively low bandwidth andstorage devices acting as bandwidth amplification devices, such aspeer-to-peer (P2P) devices. Since the fragments distributed between thetwo types of devices are unique, any combination of devices, from bothtypes, can be used to obtain a decodable set of fragments, if thecombination of devices stores a decodable set of fragments. In oneembodiment, there are at least ten times more bandwidth amplificationdevices than high bandwidth servers, and the redundancy factor used indecoding the fragments is greater than 10. In this case, the servers canbe used all or most of the time, and the bandwidth amplification devicescan be used from time to time, according to bandwidth requirements, andaccording to the availability of the bandwidth amplification devices. Inone embodiment, the processes of obtaining a fragment from a server andfrom a bandwidth amplification device are essentially the same, and thefragments are essentially identical in construction and format. In oneembodiment, the high redundancy factor needed to support a large hybridarray of servers and bandwidth amplification devices is achieved usingrateless coding techniques.

FIG. 39 illustrates one embodiment in which fractional-storage servers3799 a to 3799 c store a first portion of rateless-coded fragments; anda large number of P2P bandwidth amplification devices 3799 d to 3799 jstore a second portion of the rateless-coded fragments. Decodable setsof fragments can be obtained from combinations of fragments from thefirst and second portions of the fragments. Optionally, the fragmentsare obtained approximately only from P2P devices serviced by ISPs 3771,3772 having communication lines estimated not to be overloaded byadditional fragment traffic.

In one embodiment, the P2P devices are spread over different time zonesspanning at least three hours, and the fragments are obtainedapproximately only from P2P devices located in time zones in which thecurrent local Internet traffic is relatively low in comparison to peaklocal traffic.

In some embodiments, the push protocol is implemented using one or moresub-transmissions. Optionally, a push protocol transmission isimplemented using multiple sub-transmissions, each transporting afraction of the fragments transmitted by the push protocol transmission.A sub-transmission may be transported using an IP stream such as RTP, anHTTPS session, or any other form of transporting a sequence of fragmentsbetween a source server and a destination assembling device.

In one embodiment, an assembling device starts retrieving fragmentsusing only fragment pull protocol processes, and then, when concludingthat a specific server is responsive enough, instructs it to startsending a push-transmission for the remaining segments. In this case,the assembling device may start with pure pull-protocol based fragmentretrieval, and gradually switch to push-protocol transmissions, up tothe point that approximately all fragments are delivered usingpush-transmissions, and using the pull requests only as a means toovercome failure of obtaining specific fragments by the assemblingdevice. In one embodiment, the fragment pull protocol and the pushprotocol are used interchangeably to obtain enough fragments toreconstruct segments. In one embodiment, the assembling device may startto obtain fragments using a push protocol and then switch to a fragmentpull protocol. In one embodiment, the assembling device may use bothfragment pull protocol and push protocol to obtain fragments at the sametime, wherein the assembling device may change the ratio Fpull/Fpushon-the-fly to any value between zero and infinity, where Fpull denotesthe number of fragments associated with a certain segment that areobtained using a fragment pull protocol, and Fpush denotes the number offragments associated with the certain segment that are obtained using apush protocol.

In the claims, sentences such as “wherein the assembling device isconfigured to use a fragment pull protocol to obtain the fragments” and“wherein the assembling device is configured to use sub-transmissions toobtain the fragments” are to be interpreted as open claim language.Therefore, an assembling device configured to use a fragment pullprotocol to obtain fragments may also obtain fragments usingsub-transmissions, and vice-versa.

In the claims, a sentence such as “the erasure-coded fragments supportsource-selection diversity” is to be interpreted as fragments encodedusing any kind of erasure-code that can produce N unique fragments, fromwhich C combinations of decodable sets of fragments can be selected,wherein C is much greater than N. Standard parity checks, standardchecksums, and standard cyclic redundancy checks (CRC) are examples ofcodes that do not support source-selection diversity.

In this description, numerous specific details are set forth. However,the embodiments of the invention may be practiced without some of thesespecific details. In other instances, well-known hardware, software,materials, structures and techniques have not been shown in detail inorder not to obscure the understanding of this description. In thisdescription, references to “one embodiment” mean that the feature beingreferred to may be included in at least one embodiment of the invention.Moreover, separate references to “one embodiment” or “some embodiments”in this description do not necessarily refer to the same embodiment.Illustrated embodiments are not mutually exclusive, unless so stated andexcept as will be readily apparent to those of ordinary skill in theart. Thus, the invention may include any variety of combinations and/orintegrations of the features of the embodiments described herein.

Although some embodiments may depict serial operations, the embodimentsmay perform certain operations in parallel and/or in different ordersfrom those depicted. Moreover, the use of repeated reference numeralsand/or letters in the text and/or drawings is for the purpose ofsimplicity and clarity and does not in itself dictate a relationshipbetween the various embodiments and/or configurations discussed. Theembodiments are not limited in their applications to the details of theorder or sequence of steps of operation of methods, or to details ofimplementation of devices, set in the description, drawings, orexamples. Moreover, individual blocks illustrated in the figures may befunctional in nature and do not necessarily correspond to discretehardware elements. While the methods disclosed herein have beendescribed and shown with reference to particular steps performed in aparticular order, it is understood that these steps may be combined,sub-divided, or reordered to form an equivalent method without departingfrom the teachings of the embodiments. Accordingly, unless specificallyindicated herein, the order and grouping of the steps is not alimitation of the embodiments. Furthermore, methods and mechanisms ofthe embodiments will sometimes be described in singular form forclarity. However, some embodiments may include multiple iterations of amethod or multiple instantiations of a mechanism unless noted otherwise.For example, when a controller or an interface are disclosed in anembodiment, the scope of the embodiment is intended to also cover theuse of multiple controllers or interfaces.

Certain features of the embodiments, which may have been, for clarity,described in the context of separate embodiments, may also be providedin various combinations in a single embodiment. Conversely, variousfeatures of the embodiments, which may have been, for brevity, describedin the context of a single embodiment, may also be provided separatelyor in any suitable sub-combination.

Embodiments described in conjunction with specific examples arepresented by way of example, and not limitation. Moreover, it is evidentthat many alternatives, modifications and variations will be apparent tothose skilled in the art. It is to be understood that other embodimentsmay be utilized and structural changes may be made without departingfrom the scope of the embodiments. Accordingly, it is intended toembrace all such alternatives, modifications and variations that fallwithin the spirit and scope of the appended claims and theirequivalents.

1) A method for load-balancing fractional-storage servers, comprising:retrieving, by an assembling device using a fragment pull protocol,erasure-coded fragments associated with segments, from a set offractional-storage servers; occasionally, while retrieving thefragments, identifying at least one server from the set that is loadedto a degree requiring replacement; and replacing, using the fragmentpull protocol, the identified server with a substitute server that isnot loaded to the degree requiring replacement; wherein the substituteserver and the remaining servers of the set are capable of deliveringenough erasure-coded fragments needed in the course of reconstructingthe segments. 2) The method of claim 1, wherein the step of identifyingat least one server from the set that is loaded to a degree requiringreplacement is based on receiving an indication that the at least oneserver is loaded to a degree requiring replacement. 3) The method ofclaim 2, further comprising sending the indication, by the server thatis loaded to the degree requiring replacement, in response to a fragmentrequest or a load query. 4) The method of claim 1, further comprisingmeasuring the latency between the assembling device and at least one ofthe servers in the set, and identifying the at least one server that isloaded to a degree requiring replacement based on the measured latency,whereby increased latency may suggest that the server is loaded to adegree requiring replacement. 5) The method of claim 1, furthercomprising measuring the variance in the latency in responding tofragment requests, and identifying the at least one server that isloaded to a degree requiring replacement based on the latency variance,whereby increased latency variance may suggest that the server is loadedto a degree requiring replacement. 6) The method of claim 1, furthercomprising obtaining, from time to time, indications about servers, notin the set, which are not loaded to the degree requiring replacement;and selecting the substitute server using the obtained indications. 7)The method of claim 6, wherein the substitute server is approximatelythe least loaded server, and the erasure-coded fragments supportsource-selection diversity. 8) The method of claim 1, wherein theidentified server approximately does not have enough unutilizedbandwidth to support a fragment request. 9) The method of claim 1,wherein the identified server approximately does not have enoughprocessing resources available to support a fragment request. 10) Themethod of claim 1, wherein the erasure-coding is rateless-codingpotentially resulting in fragments having a limitless redundancy factor,whereby high redundancy increases the number of servers from which thesubstitute server can be selected. 11) A method for load balancingfractional-storage servers, comprising: retrieving, by assemblingdevices using a fragment pull protocol, erasure-coded fragments from afirst set of fractional-storage servers; identifying a second set ofservers that are able to increase their current fragment deliverythroughput; identifying, while retrieving the fragments, at least oneserver from the first set that is loaded beyond a certain threshold; andreplacing the server loaded beyond the certain threshold with a serverselected from the second set according to an algorithm. 12) The methodof claim 11, wherein the algorithm comprises approximately randomselection of the replacement server, and the erasure-coded fragmentssupport source-selection diversity. 13) The method of claim 11, whereinthe algorithm comprises selecting the least loaded server as thereplacement server, and the erasure-coded fragments supportsource-selection diversity. 14) The method of claim 11, wherein thealgorithm comprises selecting the server having approximately the lowestlatency in relation to the assembling device as the replacement server.15) The method of claim 14, further comprising obtaining data regardingthe router hop-count between the assembling device and the servers, andderiving the latencies from the hop-count data; whereby high hop-countindicates high latency. 16) The method of claim 11, further comprisingmeasuring the latencies by the assembling device, and selecting theserver having approximately the lowest latency variance in relation tothe assembling device as the replacement server. 17) The method of claim11, wherein the servers of the second set of servers are able toincrease their current fragment delivery throughput by using currentlyunutilized bandwidth. 18) The method of claim 11, wherein the servers ofthe second set are able to increase their current fragment deliverythroughput by using currently unutilized computational resources. 19) Asystem comprising: at least 100 fractional-storage CDN servers connectedto the public Internet; the servers store, at an average storagegain >5, erasure-coded fragments associated with approximatelysequential segments of streaming contents, and are configured to respondwith fragments to fragment pull protocol requests issued by assemblingdevices; wherein the erasure-coded fragments support source-selectiondiversity, and the system is configured to achieve load-balancing bydirecting the fragment pull protocol requests towards the less loadedservers. 20) The system of claim 19, wherein the system enables eachassembling device to select the least loaded servers by itself.